| An improved P300-based brain-computer interface H Serby, E Yom-Tov, GF Inbar IEEE Transactions on neural systems and rehabilitation engineering 13 (1), 89-98, 2005 | 500 | 2005 |
| Models of user engagement J Lehmann, M Lalmas, E Yom-Tov, G Dupret User Modeling, Adaptation, and Personalization: 20th International …, 2012 | 370 | 2012 |
| Microsoft malware classification challenge R Ronen, M Radu, C Feuerstein, E Yom-Tov, M Ahmadi arXiv preprint arXiv:1802.10135, 2018 | 366 | 2018 |
| Milepost gcc: Machine learning enabled self-tuning compiler G Fursin, Y Kashnikov, AW Memon, Z Chamski, O Temam, M Namolaru, ... International journal of parallel programming 39, 296-327, 2011 | 312 | 2011 |
| Measuring user engagement M Lalmas, H O'Brien, E Yom-Tov Springer Nature, 2022 | 278 | 2022 |
| What makes a query difficult? D Carmel, E Yom-Tov, A Darlow, D Pelleg Proceedings of the 29th annual international ACM SIGIR conference on …, 2006 | 274 | 2006 |
| A Streaming Parallel Decision Tree Algorithm. Y Ben-Haim, E Tom-Tov Journal of Machine Learning Research 11 (2), 2010 | 270 | 2010 |
| Learning to estimate query difficulty: including applications to missing content detection and distributed information retrieval E Yom-Tov, S Fine, D Carmel, A Darlow Proceedings of the 28th annual international ACM SIGIR conference on …, 2005 | 270 | 2005 |
| Estimating the query difficulty for information retrieval D Carmel, E Yom-Tov Morgan & Claypool Publishers, 2010 | 244 | 2010 |
| 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 | 238 | 2010 |
| Automatic churn prediction S Fine, E Yom-Tov, Y Richter US Patent App. 12/790,850, 2011 | 194 | 2011 |
| Classification of finger activation for use in a robotic prosthesis arm D Peleg, E Braiman, E Yom-Tov, GF Inbar IEEE Transactions on Neural Systems and Rehabilitation Engineering 10 (4 …, 2002 | 177 | 2002 |
| MILEPOST GCC: machine learning based research compiler G Fursin, C Miranda, O Temam, M Namolaru, A Zaks, B Mendelson, ... GCC summit, 2008 | 162 | 2008 |
| Encouraging physical activity in patients with diabetes: Intervention using a reinforcement learning system E Yom-Tov, G Feraru, M Kozdoba, S Mannor, M Tennenholtz, I Hochberg Journal of medical Internet research 19 (10), e338, 2017 | 161 | 2017 |
| Tracking COVID-19 using online search V Lampos, MS Majumder, E Yom-Tov, M Edelstein, S Moura, Y Hamada, ... NPJ digital medicine 4 (1), 17, 2021 | 139 | 2021 |
| Applying multiple data collection tools to quantify human papillomavirus vaccine communication on Twitter PM Massey, A Leader, E Yom-Tov, A Budenz, K Fisher, AC Klassen Journal of medical Internet research 18 (12), e318, 2016 | 127 | 2016 |
| The impact of delay announcements on hospital network coordination and waiting times J Dong, E Yom-Tov, GB Yom-Tov Management Science 65 (5), 1969-1994, 2019 | 124 | 2019 |
| Feature selection for the classification of movements from single movement-related potentials E Yom-Tov, GF Inbar IEEE Transactions on neural systems and rehabilitation engineering 10 (3 …, 2002 | 119 | 2002 |
| Postmarket drug surveillance without trial costs: discovery of adverse drug reactions through large-scale analysis of web search queries E Yom-Tov, E Gabrilovich Journal of medical Internet research 15 (6), e2614, 2013 | 118 | 2013 |
| Pro-anorexia and pro-recovery photo sharing: A tale of two warring tribes E Yom-Tov, L Fernandez-Luque, I Weber, SP Crain Journal of medical Internet research 14 (6), e2239, 2012 | 110 | 2012 |
David CarmelPrincipal Applied Scientist, Amazon, Haifaamazon.com의 이메일 확인됨
