| Never-ending learning T Mitchell, W Cohen, E Hruschka, P Talukdar, B Yang, J Betteridge, ... Communications of the ACM 61 (5), 103-115, 2018 | 1040 | 2018 |
| Learning a neural semantic parser from user feedback S Iyer, I Konstas, A Cheung, J Krishnamurthy, L Zettlemoyer arXiv preprint arXiv:1704.08760, 2017 | 280 | 2017 |
| Neural semantic parsing with type constraints for semi-structured tables J Krishnamurthy, P Dasigi, M Gardner Proceedings of the 2017 Conference on Empirical Methods in Natural Language …, 2017 | 205 | 2017 |
| Jointly learning to parse and perceive: Connecting natural language to the physical world J Krishnamurthy, T Kollar Transactions of the Association for Computational Linguistics 1, 193-206, 2013 | 186 | 2013 |
| Incorporating vector space similarity in random walk inference over knowledge bases M Gardner, P Talukdar, J Krishnamurthy, T Mitchell Proceedings of the 2014 conference on empirical methods in natural language …, 2014 | 174 | 2014 |
| Weakly Supervised Training of Semantic Parsers J Krishnamurthy, TM Mitchell | 158 | 2012 |
| Instructable intelligent personal agent A Azaria, J Krishnamurthy, TM Mitchell Thirtieth AAAI conference on artificial intelligence, 2016 | 89 | 2016 |
| The MD6 hash function–a proposal to NIST for SHA-3 RL Rivest, B Agre, DV Bailey, C Crutchfield, Y Dodis, KE Fleming, A Khan, ... Submission to NIST 2 (3), 1-234, 2008 | 87 | 2008 |
| Which noun phrases denote which concepts? J Krishnamurthy, T Mitchell Proceedings of the 49th Annual Meeting of the Association for Computational …, 2011 | 47 | 2011 |
| Joint syntactic and semantic parsing with combinatory categorial grammar J Krishnamurthy, T Mitchell Proceedings of the 52nd Annual Meeting of the Association for Computational …, 2014 | 44 | 2014 |
| Vector space semantic parsing: A framework for compositional vector space models J Krishnamurthy, T Mitchell Proceedings of the Workshop on Continuous Vector Space Models and their …, 2013 | 44 | 2013 |
| Task-oriented dialogue as dataflow synthesis J Andreas, J Bufe, D Burkett, C Chen, J Clausman, J Crawford, K Crim, ... Transactions of the Association for Computational Linguistics 8, 556-571, 2020 | 40 | 2020 |
| Learning a compositional semantics for freebase with an open predicate vocabulary J Krishnamurthy, TM Mitchell Transactions of the Association for Computational Linguistics 3, 257-270, 2015 | 39 | 2015 |
| Toward Interactive Grounded Language Acqusition. T Kollar, J Krishnamurthy, GP Strimel Robotics: Science and systems 1, 721-732, 2013 | 39 | 2013 |
| An interface for targeted collection of common sense knowledge using a mixture model R Speer, J Krishnamurthy, C Havasi, D Smith, H Lieberman, K Arnold Proceedings of the 14th international conference on intelligent user …, 2009 | 32 | 2009 |
| Open-vocabulary semantic parsing with both distributional statistics and formal knowledge M Gardner, J Krishnamurthy Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 28 | 2017 |
| The MD6 hash function RL Rivest, B Agre, DV Bailey, C Crutchfield, Y Dodis, KE Fleming, A Khan, ... Cited on, 6, 2008 | 27 | 2008 |
| Structured set matching networks for one-shot part labeling J Choi, J Krishnamurthy, A Kembhavi, A Farhadi Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 26 | 2018 |
| Semantic parsing to probabilistic programs for situated question answering J Krishnamurthy, O Tafjord, A Kembhavi arXiv preprint arXiv:1606.07046, 2016 | 24 | 2016 |
| Probabilistic models for learning a semantic parser lexicon J Krishnamurthy Proceedings of the 2016 Conference of the North American Chapter of the …, 2016 | 12 | 2016 |
Tom MitchellFounders University Professor of Machine Learning, Carnegie Mellon UniversityVahvistettu sähköpostiosoite verkkotunnuksessa cs.cmu.edu
