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- 28 bytes (2 words) - 13:40, 3 September 2017
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- |Title=Sixth International Conference on Learning Representations |Field=machine learning, deep learning, learning679 bytes (83 words) - 18:18, 12 February 2020
- | Title = Workshop on Semi-supervised Learning for Natural Language Processing at NAACL HLT 2009 | Field = Machine learning7 KB (961 words) - 05:50, 14 October 2008
- and consider deep semantic processing as a serious task in - learning semantic representations from raw text7 KB (856 words) - 23:06, 14 October 2008
- dependency-style analyses, various hybrid "deep/shallow" approaches, balancing the considerations of what structure merits learning versus5 KB (683 words) - 23:07, 14 October 2008
- | Title = LREC 2008 Workshop on PARTIAL PARSING Between Chunking and Deep Parsing Between Chunking and Deep Parsing5 KB (589 words) - 23:07, 14 October 2008
- ...ture, e-Governance, e-Business, and enabling policy and regulations with a deep focus on developing countries. * Experiences and applications in areas such as: e-health, e-learning, e-agriculture, e-government, and e-participation9 KB (1,127 words) - 17:19, 26 April 2011
- | Title = Workshop on Advances in Accessing Deep Web 1st Workshop on Advances in Accessing Deep Web (ADW 2008)7 KB (875 words) - 23:10, 14 October 2008
- |Title=Seventh International Conference on Learning Representations |Field=machine learning, deep learning, learning2 KB (245 words) - 10:52, 12 May 2020
- Accessing the Deep Web (ADW 2008) and on E-Learning for Business Needs).7 KB (860 words) - 11:55, 7 January 2009
- * Norm learning and emergence <big>Area 6 – Learning and Adaptation6 KB (659 words) - 17:41, 11 February 2021
- ...duce research findings about gender and ethnic differences in teaching and learning, and then focus on alternative techniques for teaching software engineering ...ntended to provide students and participants with the ability to engage in deep technical discussions about their work. Posters provide students with a uni7 KB (892 words) - 09:16, 8 July 2020
- ...hitectures for emerging application domains such as deep learning, machine learning, relational computation, neuromorphic, quantum, etc.5 KB (580 words) - 10:32, 12 May 2020
- * Martin Vechev: Can Programming Languages Research impact Deep Learning 2.0?3 KB (402 words) - 13:23, 8 July 2020
- |Title=31st Annual Conference on Learning Theory |Field=Theoretical Aspects of Machine Learning and Related Topics3 KB (314 words) - 09:33, 1 April 2020
- *S2: Reinforcement Learning: Leveraging Deep Learning for Controls3 KB (429 words) - 10:49, 9 October 2020
- Deep/Hidden Web Web-based Learning2 KB (240 words) - 17:46, 21 July 2016
- * » fuzzy deep learning2 KB (223 words) - 17:26, 6 May 2021
- | Title = The 1st Asian Conference on Machine Learning | Field = Machine learning5 KB (607 words) - 17:03, 27 December 2015
- Web-based learning E-learning5 KB (604 words) - 17:06, 27 February 2009
- ...those technologies are changing our notion of what a meeting is. We see a deep interest in this community in understanding, augmenting, and challenging me * Learning from prototypes and experimental systems5 KB (670 words) - 17:08, 27 February 2009
- * Deep learning for multimedia retrieval * Learning and relevance feedback in multimedia retrieval3 KB (439 words) - 06:47, 17 April 2020
- ...communications, collaborative objects and the Internet of Things, machine learning, mobile and social sensing, and embedded systems design. Of special interes *Machine learning and deep learning on sensor data3 KB (412 words) - 09:52, 27 February 2020
- * Learning vector quantization * Deep neural networks5 KB (574 words) - 15:58, 6 March 2020
- ...ed diagnosis or related fields such as artificial intelligence and machine learning, to encourage growth, raising the profile of this multidisciplinary field w Machine learning including deep learning3 KB (362 words) - 08:13, 17 September 2020
- ...cessing, Databases and Information Systems, Information Retrieval, Machine Learning, Multimedia, Distributed Systems, Social Networks, Web Engineering, and Web 3rd Deep Learning for Knowledge Graphs (DL4KG2020) Workshop3 KB (394 words) - 13:28, 10 December 2020
- |Title=Eighth International Conference on Learning Representations |Field=machine learning, deep learning, learning2 KB (264 words) - 10:47, 12 May 2020
- *Conceptual Models and Machine Learning *Role of Conceptual Modeling in Social Networks, Mobile Computing, Deep Learning, Internet of Objects, Serious Games and Pedagogical Models, etc.5 KB (663 words) - 11:49, 18 February 2020
- * Enterprise Knowledge Graphs, Graph Data Management and Deep Semantics * Machine Learning & Deep Learning Techniques6 KB (872 words) - 14:00, 22 February 2020
- * Retrieval Models and Ranking (e.g., ranking algorithms, learning to rank, language models, retrieval models, combining searches, diversity a Research bridging AI and IR, especially toward deep semantics and dialog with intelligent agents, such as:8 KB (1,024 words) - 09:57, 13 May 2020
- ...ence and Semantic Web, databases, data science, data analytics and machine learning, human-computer interaction, social networks, distributed and mobile system ...ncern is amplified by the opaque nature of techniques such as deep machine learning and the ease with which they can be applies over large varieties of dataset6 KB (872 words) - 23:11, 24 February 2020
- ...obotics and perception, multiagent systems, statistical learning, and deep learning. We expressly encourage work that cuts across technical areas, or develops13 KB (1,895 words) - 16:30, 26 November 2020
- |Field=Artificial Intelligence,Neural Information Processing Systems,Deep Learning ...Processing Systems (abbreviated as NeurIPS and formerly NIPS) is a machine learning and computational neuroscience conference held every December. The conferen4 KB (561 words) - 17:31, 13 February 2020
- *Deep Learning *Machine Learning2 KB (270 words) - 11:31, 21 June 2016
- * System descriptions and best practices in linked learning ...ents who would like to discuss their ideas and get feedback before they go deep developing them.6 KB (898 words) - 14:42, 24 September 2016
- ...ence and Semantic Web, databases, data science, data analytics and machine learning, human-computer interaction, social networks, distributed and mobile system ...ncern is amplified by the opaque nature of techniques such as deep machine learning and the ease with which they can be applies over large varieties of dataset6 KB (877 words) - 23:06, 24 February 2020
- |Title=MLHPC 2016 : Machine Learning in High Performance Computing Environments Workshop |Field=machine learning, deep learning, high performance computing, supercomputing387 bytes (41 words) - 06:31, 20 September 2016
- |Title=ICLR 2017 : 5th International Conference on Learning Representations |Field=machine learning, deep learning, learning representation365 bytes (40 words) - 17:32, 19 December 2016
- ...WINVIZNN 2016 : ACCV 2016 Workshop on Interpretation and Visualization of Deep Neural Nets |Field=neural networks, machine learning, interpretability, deep learning467 bytes (56 words) - 15:07, 17 August 2016
- ...information extraction; Community detection in social networks; Mining and learning activities; Confidence-based and incomplete information ...Social graph partitioning methods; Monitoring of co-evolving data streams; Deep packet inspection systems; Ensemble-based data mining platforms; Sensors-or10 KB (1,305 words) - 00:29, 12 December 2020
- * deep learning5 KB (580 words) - 20:22, 28 January 2017
- ...large-scale data analytics of textual and graph data, large-scale machine learning systems, distributed computing (cloud, map-reduce, MPI), large-scale optimi ...ression methods, deep learning, semi-supervised learning, and unsupervised learning and clustering.2 KB (282 words) - 10:48, 8 February 2020
- |Title=ICDLT 2017 : ACM--2017 International Conference on Deep Learning Technologies (ICDLT 2017)--Ei Compendex and Scopus439 bytes (52 words) - 13:48, 25 September 2016
- |Title=ACM--ICDLT 2017 : ACM--2017 International Conference on Deep Learning Technologies (ICDLT 2017)--Ei Compendex and Scopus |Field=information technology, e-learning , machine learning, multimedia451 bytes (52 words) - 13:48, 25 September 2016
- |Title=30th Annual Conference on Learning Theory |Field=Computational Learning Theory2 KB (240 words) - 15:50, 21 May 2019
- * WS 34 Deep Learning in heterogenen Datenbeständen7 KB (852 words) - 09:34, 27 April 2017
- Workshop on Deep Learning Applications (http://www.dirf.org/intech/deep-learning-applications/) E-Learning, e-Commerce, e-Business and e-Government5 KB (631 words) - 15:09, 10 April 2017
- * System descriptions and best practices in linked learning ...ents who would like to discuss their ideas and get feedback before they go deep developing them.7 KB (988 words) - 09:50, 14 August 2019
- *Indexing and Information Extraction from the (Semantic) Deep Web *Knowledge Extraction and Ontology Learning from the Web18 KB (2,394 words) - 16:28, 29 January 2018
- |Title=Second Workshop on Semantic Deep Learning Deadline Extension for for the Second Workshop on Semantic Deep Learning (SemDeep-2)4 KB (590 words) - 10:52, 16 July 2017
- - Deep Learning for Natural Language Interaction5 KB (693 words) - 10:36, 16 July 2017
- data analytics and machine learning, social networks, distributed and mobile ...ig) data analytics, data mining, and machine learning (incl. semantic deep learning)6 KB (798 words) - 23:16, 24 February 2020
- * Reinforcement learning * Learning and memory Attention14 KB (1,941 words) - 11:55, 8 August 2017
- Machine Learning and Pattern Recognition Machine Learning and Neural Networks5 KB (673 words) - 09:53, 3 September 2017
- makes the learning of big multimedia data difficult as most of the current machine learning techniques and the requirements of our real life. In this case,3 KB (511 words) - 13:28, 28 July 2017
- |Title=HPGDML 2017 : High Performance Graph Data Mining and Machine Learning Workshop HPGDML'17: High Performance Graph Data Mining and Machine Learning Workshop6 KB (860 words) - 11:52, 8 August 2017
- deep learning and classification.6 KB (824 words) - 09:04, 3 September 2017
- EI--CCISP 2017 : EI--2017 2nd International Conference on Communication, Image and Signal ProcessingAI & Deep Learning2 KB (327 words) - 13:30, 28 July 2017
- |Title=3rd INNS Conference on Big Data and Deep Learning |Field=machine learning6 KB (824 words) - 19:42, 29 October 2020
- |Field=machine learning • Deep learning approaches for unconstrained biometric recognition,3 KB (403 words) - 13:30, 28 July 2017
- Science is about learning from your data. Thus, with the advancement in computer experience in the area of machine learning in data science and analytics.4 KB (551 words) - 11:57, 8 August 2017
- |Title=ACML 2017 : The 9th Asian Conference on Machine Learning The 9th Asian Conference on Machine Learning (ACML 2017) will take place on3 KB (347 words) - 11:52, 8 August 2017
- - Deep Learning for cyber security - Adversarial Machine Learning4 KB (626 words) - 09:30, 3 September 2017
- • Deep Learning for IoS and Urban Computing4 KB (442 words) - 10:00, 21 August 2017
- ...obotics and perception, multiagent systems, statistical learning, and deep learning. We expressly encourage work that cuts across technical areas, or develops11 KB (1,589 words) - 18:03, 26 November 2020
- and machine learning. These methods are moving out of academic and high tech values in supervised learning, or acquiring the values of missing explanatory4 KB (589 words) - 14:05, 3 December 2020
- |Field=machine learning learning as well as their applications and services for the retrieval,5 KB (623 words) - 11:57, 8 August 2017
- |Title=VSI: DL-Fusion 2018 : Special issue On “Deep Learning for Information Fusion” - Information Fusion (Elsevier) |Field=machine learning3 KB (364 words) - 13:19, 28 July 2017
- * Relevance Feedback, Active/Transfer Learning Machine Learning/Deep Learning/Data Mining5 KB (654 words) - 09:58, 21 August 2017
- * Architecture and Programming Support for Emerging Domains (Big Data, Deep * Learning)1 KB (178 words) - 10:05, 20 November 2020
- * Machine learning and deep networks for web search and data mining8 KB (1,069 words) - 08:17, 6 February 2020
- Statistical Learning Theory Online Learning, Data Stream Mining, and Dynamic Data Mining2 KB (205 words) - 12:56, 3 September 2017
- •Track 3: Artificial Intelligence, machine learning, neural networks, SVM, deep learning and classification techniques, language processing, semantic analysis,2 KB (240 words) - 13:40, 3 September 2017
- knowledge learning. Probabilistic reasoning is used to solve probability inference model imitate human process data, knowledge learning and4 KB (598 words) - 09:58, 21 August 2017
- learning in biomedical imaging and image analysis) Deep learning methods (convolutional neural network, autoencoder, deep belief3 KB (346 words) - 09:58, 21 August 2017
- * Big data systems, deep-learning systems, and other data analytics11 KB (1,364 words) - 13:23, 3 September 2017
- · Small-samples machine learning · Deep learning4 KB (484 words) - 10:00, 21 August 2017
- e-Learning and MOOCs Deep Learning and Urban Computing2 KB (269 words) - 11:57, 3 September 2017
- ...data, image and video, audio and speech, big data, natural language, deep learning12 KB (1,578 words) - 14:54, 24 September 2020
- Deep learning for Images and Video Machine learning technologies for vision3 KB (379 words) - 04:24, 1 February 2018
- ...lysis algorithms, event detection and tracking, deep neural networks, deep learning)4 KB (546 words) - 14:37, 3 August 2023
- |Title=32nd Annual Conference on Learning Theory |Field=Theoretical Aspects of Machine Learning and Related Topics3 KB (430 words) - 14:33, 9 April 2020
- *Deep Neural Networks for driver identification using accelerometer signals from *Machine learning for engineering processes7 KB (917 words) - 18:07, 17 March 2020
- |Field=Artificial Intelligence,Neural Information Processing Systems,Deep Learning781 bytes (86 words) - 18:24, 12 February 2020
- * deep learning2 KB (238 words) - 18:42, 7 March 2020
- |Title=Montreal Institute for Learning Algorithms |Field=Deep Learning1 KB (192 words) - 11:10, 6 September 2019
- |Title=31st International Conference on Algorithmic Learning Theory * Design and analysis of learning algorithms.1 KB (156 words) - 15:01, 4 March 2021
- * Deep learning for multimedia retrieval * Learning and relevance feedback in multimedia retrieval2 KB (251 words) - 14:17, 26 August 2020
- * Deep learning for graphics and simulation1 KB (133 words) - 11:23, 13 May 2020
- * Machine learning in distributed camera networks * Deep learning on embedded systems1 KB (163 words) - 11:38, 13 May 2020
- |Title=30th International Conference on Algorithmic Learning Theory * Design and analysis of learning algorithms.1 KB (170 words) - 09:05, 17 April 2020
- ...radars; Signal processing for crowd dynamics; Small-scale prosumers; Deep learning in compressed sensing; Biometric authentifiers; Quantum cellular automata; Machine learning on FPGAs; Deep learning on FPGAs; Object detection; Neural networks; Reconfigurable kernels; Cloud5 KB (556 words) - 15:23, 14 January 2021
- Topic 2: Machine Learning and Knowledge Reconstruction and Discovery: * Machine Learning2 KB (254 words) - 08:59, 14 April 2020
- |Title=12th International Conference on Learning and Intelligent Optimization The 12th International Conference on Learning and Intelligent Optimization (LION)3 KB (398 words) - 09:01, 22 July 2020
- ...ion, processing, and analysis; Compressive sensing (sparse sampling); Deep learning (graphical inference algorithms); High speed video acquisition, architectur ..., feature detections, bio-inspired techniques; Pattern recognition; Social learning models, Bayesian signal processing; Cognitive information processing; Biome10 KB (1,215 words) - 14:46, 19 April 2020
- ...antum-inspired optimization; Automated (industrial) assembly environments; Deep neural networks; Multimodal knowledge of the brain; Self-organization in M2 ...Intelligent robots; Self-reconfigurable mobile robots; Humanoid imitative learning; Robots in unknown environments; Human centric robots; Adjustable robust op16 KB (1,897 words) - 12:31, 18 May 2020
- ...for the semantic Web; Online Web experiments; Web template extracting; Web deep browsing; Discovering Web content vulnerabilites; Ad hoc exploratory search ...; Sparse user-generated data; Human-centered entity linking; Transfer deep learning; Mobile Web cache; RDF data; Web private-preservation; Web vulnerabilities11 KB (1,390 words) - 12:35, 18 May 2020
- ...ning approaches to recommendation algorithms (deep learning, reinforcement learning, etc.)1 KB (141 words) - 07:08, 18 May 2020
- * Data-driven reasoning and learning * Deep learning for agent systems998 bytes (127 words) - 11:28, 26 August 2020
- original approaches (such as Artificial Intelligence (AI) and Machine Learning (ML)), to new applications (such as wearable ...l systems for communications, video and multimedia, machine-learning, deep-learning, neuromorphism, cryptographics, security and trusted computing, special-fun6 KB (673 words) - 09:29, 6 May 2020
- ...; systems for communications, video and multimedia, machine-learning, deep-learning, neuromorphism, cryptographics, special function acceleration, processing-i5 KB (629 words) - 09:36, 6 May 2020