| Document clustering using word clusters via the information bottleneck method N Slonim, N Tishby Proceedings of the 23rd annual international ACM SIGIR conference on …, 2000 | 695 | 2000 |
| Agglomerative information bottleneck N Slonim, N Tishby Advances in neural information processing systems, 617-623, 2000 | 590 | 2000 |
| A universal framework for regulatory element discovery across all genomes and data types O Elemento, N Slonim, S Tavazoie Molecular cell 28 (2), 337-350, 2007 | 395 | 2007 |
| Unsupervised document classification using sequential information maximization N Slonim, N Friedman, N Tishby Proceedings of the 25th annual international ACM SIGIR conference on …, 2002 | 373 | 2002 |
| The power of word clusters for text classification N Slonim, N Tishby 23rd European Colloquium on Information Retrieval Research 1, 200, 2001 | 323 | 2001 |
| The information bottleneck: Theory and applications N Slonim Hebrew University of Jerusalem, 2002 | 310 | 2002 |
| Show me your evidence-an automatic method for context dependent evidence detection R Rinott, L Dankin, C Alzate, MM Khapra, E Aharoni, N Slonim Proceedings of the 2015 conference on empirical methods in natural language …, 2015 | 296 | 2015 |
| Information-based clustering N Slonim, GS Atwal, G Tkačik, W Bialek Proceedings of the National Academy of Sciences 102 (51), 18297-18302, 2005 | 294 | 2005 |
| Glucose regulates transcription in yeast through a network of signaling pathways S Zaman, SI Lippman, L Schneper, N Slonim, JR Broach Molecular systems biology 5 (1), 245, 2009 | 287 | 2009 |
| Context dependent claim detection R Levy, Y Bilu, D Hershcovich, E Aharoni, N Slonim Proceedings of COLING 2014, the 25th International Conference on …, 2014 | 284 | 2014 |
| Active learning for BERT: an empirical study LE Dor, A Halfon, A Gera, E Shnarch, L Dankin, L Choshen, M Danilevsky, ... Proceedings of the 2020 conference on empirical methods in natural language …, 2020 | 241 | 2020 |
| Predicting customer churn in mobile networks through analysis of social groups Y Richter, E Yom-Tov, N Slonim Proceedings of the 2010 SIAM international conference on data mining, 732-741, 2010 | 241 | 2010 |
| An autonomous debating system N Slonim, Y Bilu, C Alzate, R Bar-Haim, B Bogin, F Bonin, L Choshen, ... Nature 591 (7850), 379-384, 2021 | 238 | 2021 |
| Stance classification of context-dependent claims R Bar-Haim, I Bhattacharya, F Dinuzzo, A Saha, N Slonim Proceedings of the 15th Conference of the European Chapter of the …, 2017 | 216 | 2017 |
| Data clustering by markovian relaxation and the information bottleneck method N Tishby, N Slonim Advances in neural information processing systems 13, 2000 | 199 | 2000 |
| A benchmark dataset for automatic detection of claims and evidence in the context of controversial topics E Aharoni, A Polnarov, T Lavee, D Hershcovich, R Levy, R Rinott, ... Proceedings of the first workshop on argumentation mining, 64-68, 2014 | 192 | 2014 |
| Method and system for evaluating a machine tool operating characteristics E Aharoni, RJ Baseman, R Kei, O Margalit, K Mackey, M Rosen-Zvi, ... US Patent 8,285,414, 2012 | 183 | 2012 |
| Multivariate information bottleneck N Friedman, O Mosenzon, N Slonim, N Tishby arXiv preprint arXiv:1301.2270, 2013 | 182 | 2013 |
| A large-scale dataset for argument quality ranking: Construction and analysis S Gretz, R Friedman, E Cohen-Karlik, A Toledo, D Lahav, R Aharonov, ... Proceedings of the AAAI Conference on Artificial Intelligence 34 (05), 7805-7813, 2020 | 135 | 2020 |
| From arguments to key points: Towards automatic argument summarization R Bar-Haim, L Eden, R Friedman, Y Kantor, D Lahav, N Slonim arXiv preprint arXiv:2005.01619, 2020 | 111 | 2020 |
Nir FriedmanProfessor of Computer Science and Medicine, Hebrew Universitymail.huji.ac.il의 이메일 확인됨