| Improved algorithms for linear stochastic bandits Y Abbasi-Yadkori, D Pál, C Szepesvári Advances in neural information processing systems 24, 2011 | 2212 | 2011 |
| Impossibility theorems for domain adaptation SB David, T Lu, T Luu, D Pál Proceedings of the Thirteenth International Conference on Artificial …, 2010 | 378 | 2010 |
| Contextual multi-armed bandits T Lu, D Pál, M Pál Proceedings of the Thirteenth international conference on Artificial …, 2010 | 369 | 2010 |
| A sober look at clustering stability S Ben-David, U Von Luxburg, D Pál Learning Theory: 19th Annual Conference on Learning Theory, COLT 2006 …, 2006 | 328 | 2006 |
| Agnostic Online Learning. S Ben-David, D Pál, S Shalev-Shwartz COLT 3, 1, 2009 | 211 | 2009 |
| Online-to-confidence-set conversions and application to sparse stochastic bandits Y Abbasi-Yadkori, D Pal, C Szepesvari Artificial Intelligence and Statistics, 1-9, 2012 | 198 | 2012 |
| Estimation of Rényi entropy and mutual information based on generalized nearest-neighbor graphs D Pál, B Póczos, C Szepesvári Advances in neural information processing systems 23, 2010 | 197 | 2010 |
| Coin betting and parameter-free online learning F Orabona, D Pál Advances in Neural Information Processing Systems 29, 2016 | 190 | 2016 |
| Does Unlabeled Data Provably Help? Worst-case Analysis of the Sample Complexity of Semi-Supervised Learning. S Ben-David, T Lu, D Pál COLT, 33-44, 2008 | 167 | 2008 |
| Partial monitoring—classification, regret bounds, and algorithms G Bartók, DP Foster, D Pál, A Rakhlin, C Szepesvári Mathematics of Operations Research 39 (4), 967-997, 2014 | 149 | 2014 |
| General auction mechanism for search advertising G Aggarwal, S Muthukrishnan, D Pál, M Pál Proceedings of the 18th international conference on World wide web, 241-250, 2009 | 143 | 2009 |
| Stability of k-Means Clustering S Ben-David, D Pál, HU Simon Learning Theory: 20th Annual Conference on Learning Theory, COLT 2007, San …, 2007 | 129 | 2007 |
| Scale-free online learning F Orabona, D Pál Theoretical Computer Science 716, 50-69, 2018 | 121 | 2018 |
| Online least squares estimation with self-normalized processes: An application to bandit problems Y Abbasi-Yadkori, D Pál, C Szepesvári arXiv preprint arXiv:1102.2670, 2011 | 81 | 2011 |
| Minimax regret of finite partial-monitoring games in stochastic environments G Bartók, D Pál, C Szepesvári Proceedings of the 24th Annual Conference on Learning Theory, 133-154, 2011 | 58 | 2011 |
| Scale-free algorithms for online linear optimization F Orabona, D Pál International Conference on Algorithmic Learning Theory, 287-301, 2015 | 57 | 2015 |
| Toward a classification of finite partial-monitoring games A Antos, G Bartók, D Pál, C Szepesvári Theoretical Computer Science 473, 77-99, 2013 | 52 | 2013 |
| Adaptive feature selection: Computationally efficient online sparse linear regression under rip S Kale, Z Karnin, T Liang, D Pál International Conference on Machine Learning, 1780-1788, 2017 | 26 | 2017 |
| Learning low density separators S Ben-David, T Lu, D Pál, M Sotáková Artificial Intelligence and Statistics, 25-32, 2009 | 25 | 2009 |
| Optimal non-asymptotic lower bound on the minimax regret of learning with expert advice F Orabona, D Pál arXiv preprint arXiv:1511.02176, 2015 | 24 | 2015 |
Csaba SzepesvariDeepMind & University of Alberta確認したメール アドレス: cs.ualberta.ca