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  • * E-Learning and Web-enterprise training
    7 KB (763 words) - 12:25, 6 October 2011
  • |Title=Sixth International Conference on Learning Representations |Field=machine learning, deep learning, learning
    679 bytes (83 words) - 18:18, 12 February 2020
  • ..., geospatial, space/; XML-data and process /data warehouse, workflow, web, learning, control/;
    11 KB (1,371 words) - 12:28, 18 May 2020
  • * [[Organizes::E-Learning 2.0 - DELFI 2008]]
    1 KB (163 words) - 12:11, 24 September 2008
  • ** Learning, knowledge sharing, collaboration, control or conflict in F/OSS projects ** Knowledge management, e-learning and F/OSS
    10 KB (1,349 words) - 16:42, 24 September 2008
  • * E-Learning, E-Commerce, E-Society, etc.
    34 KB (4,565 words) - 22:20, 10 January 2018
  • * E-Learning, E-Commerce, E-Society, etc.
    8 KB (1,037 words) - 22:20, 10 January 2018
  • * E-Learning, E-Commerce, E-Society, etc.
    9 KB (1,189 words) - 22:20, 10 January 2018
  • * E-Learning, E-Commerce, E-Society, etc.
    26 KB (3,456 words) - 22:20, 10 January 2018
  • * Distance Learning Systems
    10 KB (1,263 words) - 22:20, 10 January 2018
  • * Distance Learning Systems
    12 KB (1,537 words) - 22:19, 10 January 2018
  • ...* CKME09 - 2nd Workshop on the Convergence of Knowledge Management and E-Learning
    1 KB (158 words) - 13:01, 2 March 2012
  • * Distance Learning Systems
    8 KB (1,040 words) - 22:20, 10 January 2018
  • |Title=25th International Conference On Machine Learning |Field=Machine learning
    5 KB (573 words) - 17:33, 26 September 2016
  • |Title=International Conference on Machine Learning |Field=Machine learning
    295 bytes (40 words) - 09:18, 26 February 2020
  • |Title=26th International Conference On Machine Learning |Field=Machine learning
    5 KB (679 words) - 08:09, 11 July 2019
  • | Title = Workshop on Semi-supervised Learning for Natural Language Processing at NAACL HLT 2009 | Field = Machine learning
    7 KB (961 words) - 05:50, 14 October 2008
  • ...vestigation of technological and methodological issues related not only to learning and play, but also to social awareness of young people in relationship to e
    5 KB (631 words) - 05:50, 14 October 2008
  • [[Category:Machine learning]]
    2 KB (251 words) - 22:20, 14 October 2008
  • | Acronym = IADIS e-Learning 2009 | Title = IADIS International Conference e-Learning 2009
    4 KB (477 words) - 17:18, 14 October 2008
  • * Computational Intelligence/Learning
    3 KB (427 words) - 16:42, 14 October 2008
  • ...ation, learning, and programming: Bayesian techniques, modeling, imitation learning, programming by demonstration.
    3 KB (459 words) - 17:26, 14 October 2008
  • * Learning mechanisms in games
    6 KB (722 words) - 17:32, 14 October 2008
  • ...e vision, active vision, spatial reasoning, 2D and 3D modeling, perceptual learning.
    2 KB (268 words) - 17:47, 14 October 2008
  • IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL 2009)
    3 KB (376 words) - 17:47, 14 October 2008
  • ...ms: ReinforcementLearning, BayesianTechniques, Graphical Models, Imitation Learning, Programming by Demonstration, Diagnostics
    2 KB (227 words) - 16:21, 28 June 2009
  • approaches, collocational corpus analysis and machine learning; researchers understanding/summarization and ontology learning.
    6 KB (857 words) - 04:56, 15 September 2009
  • This workshop is focused on the relevance of computational learning fields of NLP, machine learning, artificial intelligence,
    7 KB (888 words) - 21:58, 14 October 2008
  • | Title = NIPS Workshop on Learning over Empirical Hypothesis Spaces | Field = Machine learning
    3 KB (477 words) - 21:46, 14 October 2008
  • * Learning through Persuasion * Education & Learning
    8 KB (989 words) - 20:13, 22 February 2009
  • |Title=IADIS International Conference Mobile Learning 2009 ...ed Content & Mobile Technologies: From Consumers to Creators bypassing the Learning opportunity?
    5 KB (695 words) - 15:31, 16 February 2009
  • • Machine learning for communication systems
    6 KB (731 words) - 10:33, 14 August 2023
  • ...dio networks: low power signal processing methods, applications of machine learning Streaming video: learning from video, techniques for in-network modulation
    11 KB (1,385 words) - 17:48, 14 October 2008
  • * e-Learning, e-Commerce and e-Society Applications
    8 KB (1,026 words) - 17:48, 14 October 2008
  • | Title = Optimization for Machine Learning (NIPS Workshop 2008) | Field = Machine learning
    2 KB (214 words) - 21:28, 14 October 2008
  • ...l be achieved within the chosen time period and the indication of the main learning outcomes. Proposals should also include contact information (name, email, a
    11 KB (1,527 words) - 10:03, 19 February 2021
  • ...cs, randomness in computing, parallel and distributed computation, machine learning, applications of logic, algorithmic algebra and coding theory, computationa
    6 KB (869 words) - 20:22, 22 February 2009
  • * Machine Learning for NLP
    3 KB (368 words) - 02:02, 12 September 2019
  • * Computational mechanisms of learning and memory; * Learning mechanisms (e.g., stability, personalized user/student models);
    6 KB (692 words) - 23:59, 30 May 2016
  • [[Category:Computer-based learning]]
    359 bytes (38 words) - 00:55, 2 February 2009
  • ...onal linguistics, as well as computational linguists who are interested in learning about the particular linguistic challenges posed by African languages. ...information extraction, information retrieval, computer-assisted language learning and question answering.
    6 KB (852 words) - 21:56, 14 October 2008
  • * Pervasive Learning, Games, Entertainment
    7 KB (942 words) - 20:05, 14 October 2008
  • | Title = The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases | Field = Machine learning
    1 KB (142 words) - 11:39, 17 October 2008
  • * Distance learning/training related to design
    5 KB (674 words) - 20:05, 14 October 2008
  • education and learning systems, assistive technologies, digital entertainment) - Statistical and machine learning techniques for language processing
    4 KB (570 words) - 14:02, 4 June 2020
  • There has been growing interest over the last few years in learning text). The family of techniques enabling such learning is usually
    6 KB (796 words) - 21:57, 14 October 2008
  • * Adapting existing NLP tools to the CH and SHE domains: machine learning and semantic web technologies
    7 KB (931 words) - 21:55, 14 October 2008
  • * Relevance feedback and learning systems
    2 KB (295 words) - 07:56, 14 April 2011
  • ...s, collaboration, networking) that allow the individual for organizing her learning in a very personal way. They offer a construction set of small services to ...ment of service-oriented approaches to supporting knowledge management and learning together to go one step further beyond the enthusiasm about Knowledge Manag
    7 KB (872 words) - 20:05, 14 October 2008
  • ...val systems, geographic information systems, knowledge management systems, learning systems, multicriteria systems. ...e interfaces, collaborative systems, intelligent web mining, e-commerce, e-learning, e-business, bioinformatics, evolvable systems, virtual humans, designer dr
    3 KB (433 words) - 20:05, 14 October 2008
  • # Semantic Web for e-business, e-science, e-government, and e-learning # Machine learning and human language technologies for the Semantic Web
    4 KB (450 words) - 20:05, 14 October 2008
  • * Computational Learning Theory * Machine Learning and Data Mining
    2 KB (216 words) - 20:05, 14 October 2008
  • • E-learning, Multimedia conferencing, internet phones, and mail
    5 KB (530 words) - 10:27, 24 June 2011
  • * Machine Learning
    8 KB (1,068 words) - 21:43, 26 February 2011
  • - Collaborative Learning - Virtual Learning Environments and Issues
    6 KB (780 words) - 20:06, 14 October 2008
  • Learning and Adaptive Sensor Fusion Machine Learning
    3 KB (359 words) - 20:06, 14 October 2008
  • | Field = Machine learning ...des, but is not limited to, fundamental issues, representation, inference, learning, and decision making in qualitative and numeric paradigms.
    3 KB (321 words) - 20:06, 14 October 2008
  • - graph based learning, - graph learning and clustering,
    3 KB (344 words) - 00:44, 15 October 2008
  • | Title = First International Conference on e-Learning and Distance Learning
    459 bytes (48 words) - 21:09, 14 October 2008
  • Machine Learning
    6 KB (708 words) - 22:49, 14 October 2008
  • Robot-team learning
    3 KB (379 words) - 22:42, 4 February 2009
  • * Relevance feedback and active learning approaches for
    5 KB (575 words) - 22:45, 14 October 2008
  • * Collaborative e-education, e-learning, and collaborative computing in large scale digital libraries
    6 KB (674 words) - 22:45, 14 October 2008
  • ...ty, for entertainment and/or to socialize, and those seniors users who are learning the new technologies to improve their quality of life.
    3 KB (502 words) - 22:53, 14 October 2008
  • * AI & machine learning algorithms
    3 KB (312 words) - 22:53, 14 October 2008
  • ...certain patterns are difficult or impossible to acquire even from perfect learning data;
    4 KB (516 words) - 23:00, 14 October 2008
  • �?� Cooperative learning,
    4 KB (468 words) - 22:54, 14 October 2008
  • * Learning and training for HCI
    3 KB (322 words) - 22:41, 4 February 2009
  • E-Learning and e-Teaching E-Learning
    9 KB (1,240 words) - 22:56, 14 October 2008
  • | Title = 6th International Conference on Human System Learning | Field = Machine learning
    3 KB (349 words) - 22:56, 14 October 2008
  • Computer-based Learning Support for Creativity and Learning
    2 KB (304 words) - 22:56, 14 October 2008
  • ...008 brings also a suite of specific domain applications, such as gaming, e-learning, social, medicine, teleconferencing and engineering.
    3 KB (371 words) - 12:58, 7 January 2021
  • Robot-team learning
    2 KB (353 words) - 22:42, 4 February 2009
  • - machine learning and algorithms for natural language;
    6 KB (743 words) - 22:59, 14 October 2008
  • ...nguage with non-academic areas, interdisciplinary collaborations, language learning communities, education and language policy, and non-traditional disseminati
    4 KB (601 words) - 23:00, 14 October 2008
  • ...riod of origin (for example statistical and rule-based approaches, machine learning approaches, computer-aided lexicography).
    6 KB (772 words) - 23:00, 14 October 2008
  • ...e Acquisition (e.g. Natural and Instructed L2 Learning, Child and Adult L2 Learning, Problems in Migrant Education) ...anguage Teaching and Teacher Education (e.g. Methodology, Syllabus Design, Learning and Teaching Materials)
    3 KB (389 words) - 23:00, 14 October 2008
  • - machine learning for natural language;
    8 KB (1,140 words) - 00:14, 28 February 2020
  • tools for language learning;
    5 KB (647 words) - 23:00, 14 October 2008
  • ...ference is intended as a venue for exchanging ideas and methodologies, for learning about different perspectives, and most importantly, for stimulating discuss
    4 KB (570 words) - 23:00, 14 October 2008
  • ...tic anthropology, discourse studies, pragmatics, ethnography, and language learning and teaching) are welcome. The main working language of the conference is E
    2 KB (199 words) - 23:00, 14 October 2008
  • * The role of learning in language change * Mathematical and computational models of language learning and evolution
    5 KB (668 words) - 23:00, 14 October 2008
  • * Statistical and machine learning techniques for language processing, including
    10 KB (1,326 words) - 23:19, 13 December 2017
  • | Title = World Englishes and Second Language Teaching and Learning
    516 bytes (56 words) - 23:01, 14 October 2008
  • | Title = 25th Conference of English Teaching and Learning
    570 bytes (65 words) - 23:01, 14 October 2008
  • learning; learner corpora; testing; teacher education;
    3 KB (410 words) - 23:01, 14 October 2008
  • ...scussed: the development of emotion, the effects of fatigue in working and learning, the affective modulation of cognitive processes, as well as the abnormal d
    4 KB (530 words) - 23:01, 14 October 2008
  • - grammatical inference and algorithmic learning
    6 KB (788 words) - 23:01, 14 October 2008
  • ...to support this natural language understanding challenge and on the use of learning methods in this context. RTE has fostered an active and growing community o ...y/subsumption metrics - Tree-based distances and transformations - Machine learning - Logical inference using theorem provers
    3 KB (476 words) - 23:01, 14 October 2008
  • ...ching Japanese as a second/foreign language and computer-assisted language learning (CALL) technology.
    1 KB (182 words) - 23:01, 14 October 2008
  • ...properties of semantic theories, philosophical foundations, evolution and learning of language).''
    1 KB (143 words) - 19:12, 12 November 2020
  • The psycholinguistic and cognitive processes underlying the learning of a practitioners involved in language pedagogy, i.e. Foreign Language Learning
    9 KB (1,256 words) - 10:56, 20 November 2020
  • ...corpora of non-native speech could be used to augment and improve language learning applications in laboratory and commercial environments.
    2 KB (280 words) - 23:03, 14 October 2008
  • Methods can stem from, but are not limited to, the areas of Machine Learning, Statistics, Data Mining, Artificial Intelligence, and (Interactive) Visual [[Category:Machine learning]]
    2 KB (314 words) - 23:03, 14 October 2008
  • -Intelligent Machine Learning ...event.showcfp?eventid=3636&copyownerid=1690 WikiCFP][[Category:Machine learning]]
    2 KB (231 words) - 23:03, 14 October 2008
  • Machine Learning, Knowledge Discovery and Data Mining
    7 KB (924 words) - 23:03, 14 October 2008
  • ...event.showcfp?eventid=3554&copyownerid=1513 WikiCFP][[Category:Machine learning]]
    7 KB (1,077 words) - 23:03, 14 October 2008
  • * Machine learning [[Category:Machine learning]]
    6 KB (840 words) - 16:42, 27 December 2015
  • ...tion, etc.), or describes the integration of AI technologies (e.g. machine learning, logical inference, planning, etc.) into game AI architectures.
    9 KB (1,275 words) - 14:46, 27 December 2015
  • |Field=Machine learning ...cognitive science and cognitive modeling (language, reasoning,perception, learning, consciousness,emotion, etc.)
    2 KB (199 words) - 18:55, 7 March 2020
  • ...event.showcfp?eventid=3668&copyownerid=1513 WikiCFP][[Category:Machine learning]]
    3 KB (392 words) - 23:07, 14 October 2008
  • ...aspects of artificial neural networks, computational intelligence, machine learning and related topics. Each year, around 100 specialists attend ESANN, in orde ...the field. The ESANN conferences cover artificial neural networks, machine learning, statistical information processing and computational intelligence. Mathema
    4 KB (469 words) - 23:05, 14 October 2008
  • * Active learning and experimental design * Cluster analysis and unsupervised learning
    3 KB (341 words) - 19:39, 26 February 2020
  • ...event.showcfp?eventid=3637&copyownerid=1690 WikiCFP][[Category:Machine learning]]
    569 bytes (70 words) - 11:55, 9 July 2020
  • | Title = IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning ...et/event.showcfp?eventid=3357&copyownerid=2 WikiCFP][[Category:Machine learning]]
    599 bytes (66 words) - 23:03, 14 October 2008
  • is devoted to theories, methods and applications of Data Mining, Machine Learning, Knowledge Discovery in Databases, Knowledge
    2 KB (286 words) - 11:44, 18 October 2008
  • | Field = Machine learning
    641 bytes (70 words) - 23:04, 14 October 2008
  • KDD-related areas including data mining, data warehousing, machine learning, databases, A7. Machine Learning
    2 KB (295 words) - 12:03, 18 October 2008
  • - ASP and machine learning.
    5 KB (645 words) - 23:04, 14 October 2008
  • Machine Learning Knowledge management for e-Learning & enterprise portals
    8 KB (1,111 words) - 23:04, 14 October 2008
  • T-2 Machine Learning
    1 KB (132 words) - 23:04, 14 October 2008
  • ...nference will be preceded by two INNS-NNN 2008 Symposia on Development and Learning and Computational neurogenetic modelling (24 and 25th Nov). ...et/event.showcfp?eventid=2384&copyownerid=2 WikiCFP][[Category:Machine learning]]
    5 KB (699 words) - 23:04, 14 October 2008
  • [[Category:Machine learning]]
    592 bytes (65 words) - 23:04, 14 October 2008
  • Knowledge capture through machine learning and knowledge discovery in data bases Inclusive learning
    2 KB (314 words) - 23:04, 14 October 2008
  • Intelligence / Machine Learning �conferences in the following popular
    5 KB (696 words) - 18:29, 8 November 2008
  • ...ing the more traditional areas such as Knowledge Representation, Planning, Learning, Scheduling, Perception and also not so traditional areas such as Reactive - Machine Learning
    18 KB (2,457 words) - 23:04, 14 October 2008
  • * Learning in games ...ative studies (e.g. evolved players versus human-designed players or other learning algorithms)
    2 KB (260 words) - 23:04, 14 October 2008
  • - Learning and Self-Adaptation in Multi-Agent Systems - Reinforcement Learning
    12 KB (1,601 words) - 23:04, 14 October 2008
  • ** Machine Learning and relevance feedback for finding semantics ** Inference and machine learning for semi-automatic annotation
    4 KB (490 words) - 16:48, 15 October 2008
  • ...nd IEEE International Conference on Digital Game and Intelligent Toy Based Learning
    591 bytes (67 words) - 23:04, 14 October 2008
  • * Machine learning and data mining
    2 KB (262 words) - 23:04, 14 October 2008
  • ** Machine learning and information extraction for the Semantic Web
    6 KB (854 words) - 12:05, 28 May 2016
  • ..., and hidden information. New ideas in fields such as planning, search and learning can be developed and tested using a game environment as a testbed. ...ls such as navigating on a map, acting according to a meaningful plan, and learning from previous experience, which need to be implemented using AI algorithms.
    5 KB (713 words) - 23:04, 14 October 2008
  • - Machine learning - Semantic web for e-business and e-learning
    6 KB (827 words) - 23:04, 14 October 2008
  • KR and Machine learning, Inductive logic programming, Knowledge discovery and acquisition
    3 KB (430 words) - 16:44, 4 November 2016
  • | Field = Machine learning ...t report on theoretical or methodological advances in modeling, inference, learning and decision making under uncertainty. Submissions reporting on novel and i
    4 KB (590 words) - 23:05, 14 October 2008
  • |Field=Computational Learning Theory
    247 bytes (28 words) - 14:03, 6 October 2016
  • |Field=Computational Learning Theory
    236 bytes (30 words) - 14:03, 6 October 2016
  • * Learning and adaptive sensor fusion * Machine learning
    3 KB (346 words) - 23:05, 14 October 2008
  • Supervised and unsupervised learning. Combinations of supervised and unsupervised learning.
    4 KB (572 words) - 23:05, 14 October 2008
  • * Learning and adaptivity
    4 KB (536 words) - 17:55, 10 February 2021
  • * Computational learning and complexity
    5 KB (619 words) - 18:06, 10 February 2021
  • ...e and cooperative processes. The dynamics of cognitive processes and cross-learning are of much interest, especially when decision makers are associated with d * context awareness and the effects on learning, reasoning and decision making in both humans and software agents,
    4 KB (518 words) - 14:42, 27 December 2015
  • Statistical Methods and Learning [[Category:Machine learning]]
    3 KB (339 words) - 13:28, 16 November 2020
  • Machine learning in control applications Hybrid learning systems
    5 KB (634 words) - 23:05, 14 October 2008
  • Learning
    1 KB (139 words) - 23:05, 14 October 2008
  • Machine Learning and Data Mining in Bioinformatics).
    4 KB (563 words) - 12:00, 9 July 2020
  • Learning - learning (single and multi-agent)
    2 KB (334 words) - 17:14, 12 November 2020
  • ...uestion answering and information extraction. Text Data Mining and Machine Learning for IR.
    3 KB (399 words) - 23:05, 14 October 2008
  • ...rom all KDD related areas including data mining, data warehousing, machine learning, databases, statistics, knowledge acquisition, automatic scientific discove
    2 KB (306 words) - 12:02, 18 October 2008
  • |Title=Nature Inspired Machine Learning 2007 ...let/event.showcfp?eventid=936&copyownerid=2 WikiCFP][[Category:Machine learning]]
    435 bytes (54 words) - 15:28, 16 July 2016
  • * Integration of electronic dictionaries into language learning and teaching (CALL, translator training, etc.)
    6 KB (700 words) - 23:06, 14 October 2008
  • - grammatical inference and algorithmic learning
    7 KB (994 words) - 23:06, 14 October 2008
  • * machine learning of semantic structures
    5 KB (726 words) - 17:37, 9 January 2009
  • exploit annotated data in order to make the most of machine learning - Learning features from annotated/raw corpora
    4 KB (584 words) - 23:06, 14 October 2008
  • * Learnability of features (cf. meta-level learning for
    6 KB (729 words) - 23:06, 14 October 2008
  • Question Generation is an essential component of learning environments, help systems, information seeking systems, multi-modal conver
    4 KB (533 words) - 23:06, 14 October 2008
  • * general NLP-related machine learning techniques: theory, methods and algorithms
    4 KB (487 words) - 13:10, 19 February 2020
  • *Statistical and Machine Learning Methods
    1 KB (170 words) - 14:42, 19 February 2020
  • e-Learning of translators
    4 KB (576 words) - 23:06, 14 October 2008
  • c. Morphology : significant agreement errors, no learning from corrections ..., controlled language (CLAW), standards for MT, computer-assisted language learning with MT, using interlinguas for MT, open-source MT, example-based MT, paten
    16 KB (2,200 words) - 20:51, 18 February 2021
  • ...action will be held in conjunction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases that will t ...ations from data sources. IE methods versatilely address naturally arising learning tasks where the data is generally structured, highly correlated, and freque
    4 KB (485 words) - 23:06, 14 October 2008
  • on Computational Natural Language Learning (CoNLL-2005), and PsychoCompLA-2007 thriving research agenda that applies computational learning techniques to
    8 KB (1,014 words) - 23:06, 14 October 2008
  • ...tal versus non-incremental learning, distribution-free models of learning, learning under various distributional assumptions, learnability results, complexity
    4 KB (505 words) - 23:06, 14 October 2008
  • * required user training and consultation, learning curve of non-specialists ...ased grammars, unsupervised learning, semi-automatic learning, user-driven learning (see topic 5 too)
    9 KB (1,072 words) - 23:06, 14 October 2008
  • - learning semantic representations from raw text
    7 KB (856 words) - 23:06, 14 October 2008
  • science, psycholinguistics, language learning, and ergonomics. We
    8 KB (1,099 words) - 23:06, 14 October 2008
  • - What machine learning approaches are most appropriate for this task --
    8 KB (992 words) - 23:07, 14 October 2008
  • ...is part of the Thematic Programme "Leveraging Complex Prior Knowledge for Learning" of the PASCAL-2 European Network of Excellence starting in March 2008. ...e aim of the workshop is to present and discuss recent advances in machine learning approaches to text and natural language processing that capitalize on rich
    5 KB (758 words) - 23:07, 14 October 2008
  • * Machine Learning and Data Mining: applications of ML/DM to email, including information extr
    5 KB (668 words) - 17:01, 24 February 2016
  • research but uses methods from different areas: machine learning, computer
    4 KB (468 words) - 23:07, 14 October 2008
  • recognition, speech synthesis, character recognition, e-learning,
    7 KB (831 words) - 23:07, 14 October 2008
  • ...applications. Major conferences in natural language processing and machine learning have recently witnessed a significant number of approaches that use Wikiped ...ipedia from different perspectives, including (but not limited to) machine learning, computational linguistics, information retrieval, information extraction,
    5 KB (736 words) - 23:07, 14 October 2008
  • balancing the considerations of what structure merits learning versus
    5 KB (683 words) - 23:07, 14 October 2008
  • * Probabilistic models and machine learning * Unsupervised or semi-supervised learning of linguistic knowledge
    7 KB (908 words) - 23:07, 14 October 2008
  • arguably offer a much greater potential for learning valid * machine learning techniques for inducing structured translation
    4 KB (586 words) - 23:07, 14 October 2008
  • * Knowledge representation in learning systems * Visualization of concepts in learning systems
    6 KB (825 words) - 17:06, 27 December 2015
  • �?� Computer Assisted Language Learning
    8 KB (1,096 words) - 23:07, 14 October 2008
  • machine learning, hybrid;
    5 KB (589 words) - 23:07, 14 October 2008
  • * Corpus-based techniques and analysis (including machine learning);
    5 KB (646 words) - 14:36, 15 June 2020
  • graph and optimization algorithms; Computational learning
    5 KB (698 words) - 23:08, 14 October 2008
  • - Ontology learning from legal texts, including sub-areas such as ontology customization, ontol
    7 KB (1,016 words) - 23:08, 14 October 2008
  • * new machine learning paradigms,
    2 KB (183 words) - 23:08, 14 October 2008
  • ...axonomies and Ontologies from the Web, Information Extraction with Machine Learning, Document Classification and Indexing.
    3 KB (384 words) - 23:08, 14 October 2008
  • * Machine learning, Classification, Clustering, Ranking, Filtering, Spam Detection, Topic Dete
    3 KB (401 words) - 23:08, 14 October 2008
  • * text analysis, corpora, corpus linguistics, language processing, language learning
    7 KB (1,033 words) - 23:08, 14 October 2008
  • and machine learning. These techniques facilitate the automatic (i.e. via "supervised" machine learning methods), or
    5 KB (682 words) - 09:30, 28 August 2020
  • * Experiences and applications in areas such as: e-health, e-learning, e-agriculture, e-government, and e-participation
    9 KB (1,127 words) - 17:19, 26 April 2011
  • Learning user preferences and ranking functions
    4 KB (570 words) - 11:48, 18 October 2008
  • ...from a wide range of data mining related areas such as statistics, machine learning, pattern recognition, databases and data warehousing, data visualization, k [[Category:Machine learning]]
    5 KB (634 words) - 15:36, 14 December 2008
  • | Title = The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases | Field = Machine learning
    528 bytes (56 words) - 11:38, 17 October 2008
  • | Title = Sixth International Workshop on Teaching, Learning and Assessment of Databases
    563 bytes (66 words) - 23:09, 14 October 2008
  • - E-Learning, eCommerce, e-Business and e-Government Sheridan Institute of Technology and Advanced Learning
    4 KB (595 words) - 23:09, 14 October 2008
  • * Machine learning in data integration in the life sciences
    3 KB (419 words) - 23:10, 14 October 2008
  • Aspects of the Web (SAW 2008) and on E-Learning for Business Needs).
    7 KB (875 words) - 23:10, 14 October 2008
  • * Learning user preferences and ranking functions
    4 KB (517 words) - 15:26, 16 December 2020
  • ...l services and systems in various application fields such as e-Commerce, e-Learning or transport systems. However, such systems constrained resources in terms
    2 KB (324 words) - 16:49, 16 December 2020
  • | Title = 4th Annual e-learning conference on Intelligent Interactive Learning Object Repositories ...is hosting its 4th annual e-learning conference on Intelligent Interactive Learning Object Repositories - I2LOR 2007- November 4 to 7, 2007 in Montreal, Quebe
    4 KB (503 words) - 23:11, 14 October 2008
  • 19. e-Commerce, Mobile Commerce, e-Government, e-Learning and e-Health
    2 KB (200 words) - 23:11, 14 October 2008
  • :: Machine Learning for Cognitive Radio
    6 KB (753 words) - 23:11, 14 October 2008
  • �?� Self-learning defense strategies
    5 KB (694 words) - 23:11, 14 October 2008
  • 5. Multimedia Processing for e-Learning
    4 KB (496 words) - 23:12, 14 October 2008
  • |Title=Conference on Natural Language Learning The '''23rd Conference on Computational Natural Language Learning (CoNLL) 2019'''
    650 bytes (85 words) - 11:54, 13 March 2020
  • |Title=Conference on Natural Language Learning The '''22nd Conference on Computational Natural Language Learning'''
    612 bytes (81 words) - 12:04, 13 March 2020
  • |Title=Conference on Natural Language Learning The '''21st Conference on Computational Natural Language Learning (CoNLL) 2017'''
    627 bytes (84 words) - 12:11, 13 March 2020
  • * Agent Learning Models for Autonomic Web-Services
    3 KB (415 words) - 23:13, 14 October 2008
  • * Computational Learning Theory has contributions to make with their
    7 KB (984 words) - 23:13, 14 October 2008
  • ...m counselling, to academic advising, to program planning, to collaborative learning, to tutoring, and to testing. ...ed and more accurate intelligent support can be provided, aiming at making learning easier for learners.
    6 KB (839 words) - 23:13, 14 October 2008
  • *Ranking and machine learning for ranking
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  • ...b Services technologies. It will also target potential users interested in learning about the feasibility of Semantic Web Services in market and industry.
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  • |Title=Seventh International Conference on Learning Representations |Field=machine learning, deep learning, learning
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  • | Title = Workshop on Social Information Retrieval for Technology-Enhanced Learning Workshop on Social Information Retrieval for Technology-Enhanced Learning (SIRTEL'08)
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  • * Learning
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  • ...ds to provide a forum for researchers in the field of Data Mining, Machine Learning and Artificial Intelligence, to discuss the above and other related topics ...therefore now the right time for the application of sophisticated machine learning, data mining, information retrieval, information extraction, semantic Web a
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  • - Folksonomies and Ontology learning
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  • ...International Workshop on Social and Personal Computing for Web-Supported Learning Communities
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  • * E-learning
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  • | Title = International Conference on Web-based Learning | Field = Machine learning
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  • ...sues are being addressed in this field ranging from the development of new learning approaches to the parallelization of existing algorithms. The goal of this
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  • * Learning and relevance feedback in image/video retrieval
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  • Techniques. Machine learning for IR, learning to rank, clustering, IR scalability and efficiency, adversarial IR, user
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  • * learning to rank [[Category:Machine learning]]
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  • * Machine Learning for IR
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  • | Title = Second International Workshop on Teaching and Learning of Information Retrieval Learning of Information Retrieval
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  • ...cated with the IADIS International Conference on Cognition and Exploratory Learning in Digital Age (CELDA 2008) (http://www.celda-conf.org/) - participants of
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  • * Learning and classification methodologies for document analysis systems ...et/event.showcfp?eventid=2310&amp;copyownerid=2 WikiCFP][[Category:Machine learning]]
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  • * Application of IR technology: e-commerce, e-learning, digital libraries, ubiquitous computing, bioinformatics, medical informati
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  • Machine Learning, Knowledge Acquisition
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  • ...g, scientific visualization, modeling and simulation, data mining, machine learning and pattern recognition
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  • * Machine learning for signal processing
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  • O. Statistic Learning & Pattern Recognition
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  • | Title = IEEE Workshops on Machine Learning for Signal Processing | Field = Machine learning
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  • Machine Learning and Data Mining Artificial Intelligence and Symbolic Learning
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  • | Field = Machine learning ...this series of workshops is to bring together researchers from the Machine Learning, Pattern Recognition, Signal Processing and Communications communities, in
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  • ...buted algorithms, networks and protocols, wireless communications, machine learning, and embedded systems design.
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  • Machine learning for signal processing
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  • ...duce research findings about gender and ethnic differences in teaching and learning, and then focus on alternative techniques for teaching software engineering
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  • # software engineering with computational intelligence and machine learning * Agent-based learning and knowledge discovery
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  • ...essaging systems, which are widely analyzed using graph theory and machine learning techniques. People perceive the Web increasingly as a social medium that fo
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  • | Title = 6th International Conference on Machine Learning and Data Mining | Field = Machine learning
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  • Computational Learning Theory Multi-Task Learning
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  • ...the involvement of multiple research fields such as user modeling, machine learning, intelligent information retrieval, data and text mining, statistics, compu - Machine learning techniques for personalization
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  • ...ollaborative problem solving, seeking advice, or developing competences by learning from peers. Recently, the network perspective has gained interest in the do
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  • learning, and data mining. - data mining and machine learning techniques for supervised and
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  • adaptation of well-known data mining and machine learning algorithm and data mining algorithm and machine learning methods on Web 2.0 data.
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  • recognition, machine learning, and data mining to exchange Learning and Principles and Practice of Knowledge Discovery
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  • | Field = Machine learning
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  • | Title = 6th International Workshop on Mining and Learning with Graphs ...et/event.showcfp?eventid=2713&amp;copyownerid=2 WikiCFP][[Category:Machine learning]]
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  • | Title = European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics | Field = Machine learning
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  • ...e = The Third IEEE International Workshop on Multimedia Technologies for E-Learning Multimedia Technologies for E-Learning (MTEL)
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  • (E-Learning, Entertainment, Health Care, Web2.0, SNS, etc.)
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  • - Multimedia for Learning
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  • * e-Learning in Cultural Heritage
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  • ...to see if anyone could edit it for you for a smaller fee or you could try learning the basics of flash.Another option would be using a Flash Website Builder,
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  • | Title = Third Workshop on Tackling Computer Systems Problems with Machine Learning Techniques Third Workshop on Tackling Computer Systems Problems with Machine Learning Techniques (SysML08)
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  • | Title = 3rd Annual Machine Learning Symposium | Field = Machine learning
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  • | Title = European Workshop on Reinforcement Learning | Field = Machine learning
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  • | Title = ACM SAC Special track on Relational Learning | Field = Machine learning
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  • | Title = Workshop on Preference Learning at ECML/PKDD-08 | Field = Machine learning
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  • | Title = International Conference on Machine Learning and Applications ...et/event.showcfp?eventid=2354&amp;copyownerid=2 WikiCFP][[Category:Machine learning]]
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  • ...al Intelligence; Control and Reinforcement Learning; EmergingTechnologies; Learning Theory; Neuroscience; Speech and SignalProcessing; and Visual Processing. ...scientists. The topics spana widerange of subjects including Neuroscience, Learning Algorithms andTheory, Bioinformatics, Image Processing, and Data Mining.
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  • | Field = Machine learning
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  • | Title = Workshop on Machine Learning and Automated Planning | Field = Machine learning
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  • * Learning algorithms ...et/event.showcfp?eventid=2436&amp;copyownerid=2 WikiCFP][[Category:Machine learning]]
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  • | Title = International Conference on Machine Learning and Cybernetics | Field = Machine learning
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  • | Title = 2nd Workshop on statistical and machine learning approaches to Architectures and compilation | Field = Machine learning
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  • 13. Medical Electromagnetics 33. Learning
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  • |Title=IEEE International Conference on Advanced Learning Technologies
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  • Machine Learning and Robotics
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  • ...our products and services. Just as we support the advance of knowledge and learning, we are constantly developing our own professional skills too. We strive to
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  • * Iterative Learning Control (ILC)
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  • - Dynamics and Learning for Gesture Interpretation - Visual Learning
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  • Statistical Methods and Learning
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  • ...gistration, template matching, indexing, image search, robust recognition, learning, shape-from-X, motion analysis, segmentation, active vision, CADbased visio
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  • ...xtraction, grouping and segmentation; Scene analysis; Pattern recognition; Learning in vision; Human-computer interaction; Tracking and surveillance; Biometric
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  • ...ced techniques from pattern recognition and related fields such as machine learning, computer vision and human language technology. An increasingly important a ...ons should be related to the following areas: pattern recognition, machine learning, computer vision and human language technology.
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  • ...n techniques for recognition and categorization, knowledge representation, learning, reasoning, goal specification and context awareness
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  • - Dynamics and Learning for Gesture Interpretation - Visual Learning
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  • ...technical accessibility and Internet communications. Many online classes, learning systems, university curricula, remote education, and virtual training class ...tive learning models. The generalization of successful practices on mobile learning is favoured by many national and international projects and policy synchron
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  • Learning and adaptive sensor fusion
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  • ...Tutorials (half-day or full-day sessions) are intended to provide in-depth learning on a specific topic of interest to the participants. Panel sessions are 60
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  • ...iologists by presenting cutting-edge solutions of Modeling, Computing and Learning in Biology and Life Science. We invite submissions that address conceptual - Biological Applications of Data-Mining and Machine Learning Techniques
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  • ...network, Fuzzy systems, Genetic algorithm, Evolutionary computing, Machine learning, Data mining
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  • Intelligence and Learning
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  • | Title = Workshop On Grasp and Task Learning by Imitation
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  • management, and steep learning curves. The Java programming language
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  • 1) learning/constructing ontologies for Semantic Web applications; * Learning structures from the Web for Semantic Web-enabled applications
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  • ...formation and support user-centered tasks on a variety of domains (e.g., e-learning, e-commerce, and e-government). Local knowledge is annotated into a large r
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  • * Machine learning and human language technologies for the Semantic Web ...ications of Semantic Web (e-Business, e-Science, e-Health, e-Government, e-Learning, e-Culture)
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  • * Ontology learning
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  • * E-Learning, E-Business, E-Government, and ...l be achieved within the chosen time period and the indication of the main learning outcomes. Tutorial proposals should address the following issues:
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  • * machine learning and the semantic web * e-learning
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  • Ontology Learning and Metadata Generation (e.g., HLT and ML approaches) Semantic Web for e-Business, e-Science, e-Health, e-Culture, e-Government, e-Learning and other application domains
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  • ...nagerial (information management and processes), and economical. Fostering learning is a key, and simplicity is generally an enabler for dependability.
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  • - Ontologies in e-learning and e-science
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  • * Machine learning
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  • * Pattern recognition and machine learning techniques in biomedical engineering
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  • ...hnologies are needed. The applications of artificial intelligence, machine learning,
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  • ...hitectures for emerging application domains such as deep learning, machine learning, relational computation, neuromorphic, quantum, etc.
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  • * 2020 USENIX Conference on Operational Machine Learning (OpML '20): July 30 at the Hyatt Regency Santa Clara in Santa Clara, CA, US
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  • |Title=Networked Learning Conference
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  • * Algorithms and tools that combine verification and learning
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  • * Martin Vechev: Can Programming Languages Research impact Deep Learning 2.0?
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  • |Field=Artificial intelligence,Machine learning
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  • * Computational learning theory,
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  • * Architecture applications of Machine Learning
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  • * e-Learning Ecosystems
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  • Artificial Intelligence in Engineering: Reasoning, Learning, Decision Making, Knowledge Based Systems, Expert Systems Computational Intelligence in Engineering: Machine Learning, Genetic Algorithms, Neural Nets, Fuzzy Systems, Fuzzy and Neuro-fuzzy Cont
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  • ...power quality, electric vehicle, analytical and simulation methods, and e-learning in education.
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  • ** creation, learning, population, evolution and evaluation of ontologies
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  • ...ed Learning and Teaching Strategies and Resources & The Impact of Distance Learning on the Teaching of Philosophy and Computing
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  • ?Semantic-based Virtual Organizations ?e-culture ?e-Science ?e-Business ?e-Learning ?e-Government ?Grid Security ?Sensor networks and Grid applications
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  • ...ANALCO09). Since researchers in both fields are approaching the problem of learning detailed information about the performance of particular algorithms, we exp
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  • ...cs, randomness in computing, parallel and distributed computation, machine learning, applications of logic, algorithmic algebra and coding theory, computationa
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  • Agent-based distributed ontology mapping and learning. Multi-strategy and meta-learning for cooperative information agents.
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  • | Title = International Conference on Machine Learning and Applications
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  • ...rkshop on Visual Design Languages and Applications for Technology-Enhanced Learning ...rkshop on Visual Design Languages and Applications for Technology-Enhanced Learning (VIDLATEL '08)
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  • learning of recent developments in the evolving OpenMP standard. The
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  • ...contributions influenced by other fields such as hardware design, machine learning, control theory, networking, economics, social organizations, and biologica
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  • (Formerly Learning Object Discovery & Exchange - LODE) ...eld in conjunction with the 3rd European Conference on Technology Enhanced Learning (EC-TEL'08 - http://www.ectel08.org/), Maastricht School of Management, Maa
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  • | Title = Third European Conference on Technology Enhanced Learning
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  • | Title = Workshop on E-Learning for Business needs ...d practitioners together to explore the issues and challenges related to e-Learning for business needs. We want to facilitate discussion on the topics includin
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  • | Title = IADIS International Conference E-Learning 2008
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  • | Title = 6th International Conference in Networked Learning
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  • ...CC management, online communities, automatic classification, e-commerce, e-learning, recommendation, personalization - Intelligent systems and techniques : robotics, autonomic computing, machine learning, semantic Web, etc.
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  • * Spoken language acquisition, development and learning * Applications for learning and education
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  • - Pervasive Learning
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  • ...nd management best approached? What is the impact on knowledge management, learning and risk management? Which IP, licensing and spin-off and revenue generatio Learning and knowledge management in OI
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  • |Title=European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases |Field=Machine learning
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  • The main theme of the conference is “Future Trends in Learning and Instructional Technologies”. The aim of the conference is to bring to ..., Improving classroom teaching, Pedagogical and practical issues, Teaching/learning strategies, ICT literacy in education, Information technology diffusion/int
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  • |Field=Computer-supported learning
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  • |title=International Journal on E-Learning |Field=E-Learning
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  • |Title=World Conference on E-Learning in Corporate, Government, Healthcare, & Higher Education |Field=E-Learning
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  • |Title=GI-Fachgruppe E-Learning |Field=E-Learning
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  • |Field=Computer-based learning [[Category:E-Learning]]
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  • * Concerns of individual developers in collaboration settings, such as learning, personal productivity, usability and incentives.
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  • ...saging, mobile phone, phishing, etc. /; Spam compression and recognition; Learning misuse patterns; Payment schemes; Economics of generalized spam; Tracking a
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  • |Title=International Conference on Web-based Learning |Field=Computer-based learning
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  • |Title=E-Learning Baltics 2009 |Field=E-Learning
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  • ...histicated techniques for in-depth content processing, analysis, indexing, learning, mining, searching, management, and retrieval. The International Journal of
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  • |Title=7. e-Learning Fachtagung Informatik |Field=E-Learning
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  • ** Informal Learning at the Workplace ** Graph Mining and Statistical Relational Learning
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  • |Title=31st Annual Conference on Learning Theory |Field=Theoretical Aspects of Machine Learning and Related Topics
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  • *S2: Reinforcement Learning: Leveraging Deep Learning for Controls
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  • |Title=4th International Conference on Interactive Mobile and Computer Aided Learning |Field=Computer-supported learning
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  • |Title=International Conference on Interactive Computer Aided Blended Learning ...lecting experiences and needs of Education Institutions/Organizations in e-Learning
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  • |Title=International Conference on E-Learning in the Workplace |Field=E-Learning
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  • *Demands in education and training, e-learning, b-learning, m-learning and ODL
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  • ...le = The First Workshop on Case Studies of Bayesian Statistics and Machine Learning
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  • - E-learning - Learning through reinforcement
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  • - Special Session: Software Content Creation and Teaching and Learning Strategies in Science and Engineering - Special Session: Medical e-Learning
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  • ...rvasive computer with special tracks on collaborative work, health care, e-learning, etc. In addition to technical papers, ICPCA2009 will include keynote speec Ubiquitous Learning
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  • * Virtual Learning Environments * E-learning (organized by Jacek Waliński & Przemek Krakowian)
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  • learning tools that exploit monological and dialogical argument structures
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  • o Machine learning
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  • ...rom low-level perception and attention to higher-level problem-solving and learning.
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  • - Statistical & machine learning based approaches, transliteration unit - Learning transliteration from comparable corpora
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  • o Machine learning for e-commerce applications
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  • |Title=7. e-Learning Fachtagung Informatik der Gesellschaft für Informatik Die 7. e-Learning Fachtagung Informatik
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  • * E-government, -commerce, -learning,…
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  • * Machine learning in data integration in the life sciences
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  • - Distributed Machine Learning over XML Repositories
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  • * Learning and classification
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  • - Learning and knowledge growth
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  • | Title = 18th Annual Belgian-Dutch Conference on Machine Learning | Field = Machine learning
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  • | Title = Symposium on Learning Control
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  • - temporal learning and discovery
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  • ...al distinct research communities, including knowledge engineering, machine learning, natural language processing, human-computer interaction, artificial intell * Learning apprentices
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  • - Machine Learning
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  • * Informal (social) learning and knowledge sharing in organizations
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  • learning, data mining, case-based reasoning, artificial neural networks,
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  • Learning algorithms that use non-traditional relevance judgments.
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  • Machine Learning
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  • - Machine learning approaches to search software.
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  • - Mobile Entertainment, Gaming and Learning
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  • - Machine Learning - Agents and Learning
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  • - Learning Technologies 1) Advances in Web Based Learning - AWBL 09
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  • | Title = 7th International Workshop on Mining and Learning with Graphs * SRL-2009 - International Workshop on Statistical Relational Learning
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  • | Field = Machine learning * SRL-2009 - International Workshop on Statistical Relational Learning
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  • 5. applications of rational kernels to active/statistical machine learning of finite-state models. 2.Machine Learning with Automata by Colin de la Higuera
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  • - Machine learning in control applications - Hybrid learning systems
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  • Intelligent e-Learning Multimedia
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  • - Computer Assisted Language Learning (CALL)
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  • * Education / Transfer Technologies: E-learning, IT and Wireless Technologies in the Education Process * AmI technologies: Sensor, communications, learning and algorithms
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  • Center of Excellence for Learning in Education, Science, and Technology (http://cns.bu.edu/CELEST) Development of learning systems in the human brain
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  • Charles A. Shoniregun, Sheridan Institute of Technology and Advanced Learning, Canada Victor Ralevich, Sheridan Institute of Technology and Advanced Learning, Canada
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  • * » fuzzy deep learning
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  • * evolutionary machine learning,
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  • A-07 Natural Language Learning C-05 Machine Learning
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  • Learning Algorithms Machine Learning
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  • - Machine Learning • Dr. Doina Caragea (Machine Learning and Bioinformatics Laboratory, Kansas State University, USA)
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  • | Title = ICML 2009 Workshop on Evaluation Methods for Machine Learning IV | Field = Machine learning
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  • - Computer graphics and learning.
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  • ...event.showcfp?eventid=4965&amp;copyownerid=3738 WikiCFP][[Category:Machine learning]]
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  • o Learning algorithms
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  • |Field=Machine learning
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  • - Agent Self-organization, Learning, and Adaptation - Agent Self-organization, Learning, and Adaptation
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  • | Title = The 1st Asian Conference on Machine Learning | Field = Machine learning
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  • ...uted computing; circuits and boolean functions; online algorithms; machine learning and artificial
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  • Robot Learning
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  • [[Category:Machine learning]]
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  • Web-based learning E-learning
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  • Robotics, natural language processing, reinforcement learning, neural networks, Bayesian networks, genetic algorithms, logic, rule based
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  • 3. Goals and learning objectives
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  • evolutionary learning.
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  • * Novel application of techniques from disciplines such as machine learning, computer vision, computer graphics, speech processing, networking, or huma
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  • Computitional learning theory for the Web
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  • E-Learning Ecosystems
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  • | Title = Transformative Learning and Online Education: Aesthetics, Dimensions and Concepts Transformative Learning and Online Education:
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  • learning, interaction, reasoning, programming, robust perception, mobile manipulatio - robotic learning by experimentation
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  • • Machine learning in control applications • Hybrid learning systems
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  • ...nal experience beyond learning by their inclusion within and alongside the learning environment aspects of socialising and playing.
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  • * Active Learning * Case-Based Learning
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  • This session covers: Computer Assisted Learning and Simulation Trainers, Customizing of ERP Systems using Simulation, Distr ..., Simulation of Collective Behaviour and Emergent Phenomena, Simulation of Learning and Adaptation Processes, Assessment Criteria and Assessment Methods for Si
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  • * Learning and adaptation
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  • New Library Learning Spaces
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  • * Learning from prototypes and experimental systems
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  • -Distance Learning Systems Distance Learning Systems
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  • - Innovative uses of Technology for E-Learning
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  • cognitive aesthetics, arts, psychology, e-learning, neuroengineering,
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  • | Title = Joint Workshop on Visual and Contextual Learning from Annotated Images and Videos, and Visual Scene Understanding VCL’09: Workshop on Visual and Contextual Learning from Annotated Images and Videos
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  • - Personalized mobile learning
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  • areas: machine learning, computer linguistics and psychology, user ...ategory formation, clustering, entity resolution, document classification, learning methods for ranking
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  • |Title=Conference on Natural Language Learning ...]] (pronounce as signal) is the Special Interest Group on Natural Language Learning of the [[Association for Computational Linguistics]] (ACL).
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  • evolutionary computation, machine learning and probabilistic reasoning, and
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  • - Dynamics and Learning for Gesture Interpretation - Visual Learning
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  • *E-Learning
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  • *Knowledge graph quality for machine learning applications
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  • * Deep learning for multimedia retrieval * Learning and relevance feedback in multimedia retrieval
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  • * E-learning and learning organizations
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  • |Title=IEEE International Conference on Advanced Learning Technologies |Field=E-Learning
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  • (corporate memories, e-commerce, design, tutoring/e-learning,<br/>
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  • ...g trends, and to promote discussion about the pedagogical potential of new learning and educational technologies in the academic and corporate world. 1. Information Technologies Supporting Learning
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  • - Learning User Profiles
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  • * Machine learning
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  • ...ctor Research & Development Technology Enhanced Learning at the Centre for Learning ...te for the emergence of a productive and lasting community of practice and learning that will maximally foster innovation
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  • - Models for learning trust and the evolution of trust
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  • ...nd appearance-based robotics, path and task planning, multi-robot systems, learning and adaptation, vision-based navigation, multimodal human-robot interaction
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  • #REDIRECT [[Learning Conference 2009]]
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  • ...iewed as new foundation of Software Engineering, Knowledge Management, and Learning Organization.
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  • ...event.showcfp?eventid=6269&amp;copyownerid=5802 WikiCFP][[Category:Machine learning]]
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  • | Title = IEEE Education Engineering 2010 - The Future of Global Learning Engineering Education ...career goals. Thus processing and acquiring knowledge is a key to a modern learning pedagogy, but also content creation, collaboration and community-based prac
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  • | Title = IADIS International Conference on Cognition and Exploratory Learning in Digital Age 2009 | Homepage = IADIS International Conference on Cognition and Exploratory Learning in Digital Age (CELDA 2009)
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  • ...event.showcfp?eventid=6238&amp;copyownerid=1215 WikiCFP][[Category:Machine learning]]
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  • [[Category:Machine learning]]
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  • ...or their attendance. Attendees are encouraged to take advantage of various learning opportunities, from peer networking to visiting vendors in the exhibit hall
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  • Learning
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  • | Field = Machine learning ...approaches, Web technology, mining and agents, Genetic algorithms, Machine learning,Expert systems, Hybrid systems,
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  • |Field=Machine learning ...exciting research in all areas of Neural networks and Applications,Machine Learning,Multimedia System and Applications ,Speech Processing,Image & video Signal
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  • | Title = Learning in Intelligent Systems: FLAIRS Special Track | Field = Machine learning
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  • ...ances provide the foundation for more effective interactivity in work- and learning-related activities.
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  • ...Uncertainty in Cognition, Graphical Models, Knowledge Acquisition, Machine Learning, Evolutionary Computation, Neural Networks, Data Analysis.
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  • Supervised learning. Unsupervised learning.
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  • | Title = IEEE Intelligent Systems Speicla Issue on Social Learning Call for Papers: Special Issue on Social Learning
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  •  E-commerce and e-learning
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  • * Media ontology learning
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  • | Title = Final QALL-ME (Question Answering Learning technologies in a multiLingual and Multimodal Environment) Workshop
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  • Machine Learning and Pattern Recognition
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  • e-Learning and virtual classrooms
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  • 1. Innovative learning processes
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  • .../event.showcfp?eventid=6165&amp;copyownerid=837 WikiCFP][[Category:Machine learning]]
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  • and machine learning techniques.
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  • ...ch include (but not limited to): Ubiquitous Health Care, Ubiquitous Mobile Learning, Pervasive Emergency Management, Mobile Information Systems, Wireless and N
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  • ...ssaging, mobile phone, phishing, etc. /; Spam compression and recognition; Learning misuse patterns; Payment schemes; Economics of generalized spam; Tracking a
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  • ...gnitive vision techniques for scene analysis, semantic interpretation, and learning
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  • ...gistration, template matching, indexing, image search, robust recognition, learning, shape-from-X, motion analysis, segmentation, active vision, CAD-based visi
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  • * Automatic ontology construction (ontology learning) based on patterns
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  • • Statistical machine learning techniques in biomarker discovery
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  • ...ributed algorithms, embedded systems, wireless communications, and machine learning. In addition to full-length technical papers, IPSN is very interested in sh ...buted algorithms, networks and protocols, wireless communications, machine learning, and embedded systems design.
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  • ...stems. Together with the recent progress on semantic web, scalable machine learning, and multi-modal interaction, it is now possible to build a new generation * Media ontology generation/learning/reasoning
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  • ? Mobile ad hoc learning
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  • ...age information from other sources, such as the actor data, for multi-task learning. 1. Machine Learning in Multi-source Environments
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  • ...ts; Software engineering; Pattern recognition; Neural networks and machine learning; Computer networks and internet; Parallel and distributed systems; Computer
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  • E-Learning
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  • ...iewed as new foundation of Software Engineering, Knowledge Management, and Learning Organization.
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  • Learning Organization
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  • Pattern recognition and learning
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  • ...ke to illustrate how technology can aid in the constructionist approach to learning, thinking and education.
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  • - Supervised and Unsupervised Learning
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  • ...ems; RFID tags for digital rights management; Digital rights management in learning systems; Legal policy and digital right management
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  • * E-Learning and e-Teaching * E-Learning
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  • * Machine learning in control applications * Hybrid learning systems
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  • ...ry, language models, probabilistic retrieval models, feature-based models, learning to rank, combining searches, diversity)
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  • ...stics, image analysis, scientific data management and data mining, machine learning, pattern recognition, computational evolutionary biology, computational gen - Data mining and Machine Learning
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