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  • |Title=Sixth International Conference on Learning Representations |Field=machine learning, deep learning, learning
    679 bytes (83 words) - 18:18, 12 February 2020
  • | 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
  • and consider deep semantic processing as a serious task in - learning semantic representations from raw text
    7 KB (856 words) - 23:06, 14 October 2008
  • dependency-style analyses, various hybrid "deep/shallow" approaches, balancing the considerations of what structure merits learning versus
    5 KB (683 words) - 23:07, 14 October 2008
  • | Title = LREC 2008 Workshop on PARTIAL PARSING Between Chunking and Deep Parsing Between Chunking and Deep Parsing
    5 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-participation
    9 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, learning
    2 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 Adaptation
    6 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 uni
    7 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 Topics
    3 KB (314 words) - 09:33, 1 April 2020
  • *S2: Reinforcement Learning: Leveraging Deep Learning for Controls
    3 KB (429 words) - 10:49, 9 October 2020
  • Deep/Hidden Web Web-based Learning
    2 KB (240 words) - 17:46, 21 July 2016
  • * » fuzzy deep learning
    2 KB (223 words) - 17:26, 6 May 2021
  • | Title = The 1st Asian Conference on Machine Learning | Field = Machine learning
    5 KB (607 words) - 17:03, 27 December 2015
  • Web-based learning E-learning
    5 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 systems
    5 KB (670 words) - 17:08, 27 February 2009
  • * Deep learning for multimedia retrieval * Learning and relevance feedback in multimedia retrieval
    3 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 data
    3 KB (412 words) - 09:52, 27 February 2020
  • * Learning vector quantization * Deep neural networks
    5 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 learning
    3 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) Workshop
    3 KB (394 words) - 13:28, 10 December 2020
  • |Title=Eighth International Conference on Learning Representations |Field=machine learning, deep learning, learning
    2 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 Techniques
    6 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 dataset
    6 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 develops
    13 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 conferen
    4 KB (561 words) - 17:31, 13 February 2020
  • *Deep Learning *Machine Learning
    2 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 dataset
    6 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, supercomputing
    387 bytes (41 words) - 06:31, 20 September 2016
  • |Title=ICLR 2017 : 5th International Conference on Learning Representations |Field=machine learning, deep learning, learning representation
    365 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 learning
    467 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-or
    10 KB (1,305 words) - 00:29, 12 December 2020
  • * deep learning
    5 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 Scopus
    439 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, multimedia
    451 bytes (52 words) - 13:48, 25 September 2016
  • |Title=30th Annual Conference on Learning Theory |Field=Computational Learning Theory
    2 KB (240 words) - 15:50, 21 May 2019
  • * WS 34 Deep Learning in heterogenen Datenbeständen
    7 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-Government
    5 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 Web
    18 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 Interaction
    5 KB (693 words) - 10:36, 16 July 2017

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