RS
Robert E. Schapire
cs.LGstat.MLcs.AIcs.GTmath.OCcs.DSmath.STstat.THAlgorithmscs.CL
On Valency
published · living versionsW_a7zea258·v1 · currentpublished
Contextual Bandit Learning with Predictable Rewards
with Alekh Agarwal, Miroslav Dudík, Satyen Kale, John Langford
1 version
Preprints & journals
50 papers in the corpus · 2004–2026Learning to Reason with Curriculum II: Compositional Generalization2606.27721v1 · Nived Rajaraman, Audrey Huang, Miroslav Dudik et al.2026 · 0 citationsarXiv
Learning to Reason with Curriculum I: Provable Benefits of Autocurriculum2603.18325v2 · Nived Rajaraman, Audrey Huang, Miro Dudik et al.2026 · 0 citationsarXiv
The time course of neural activity predictive of self-initiated movementvdbg8_v5 · Lucas Jeay-Bizot, Mehmet Basbug, Uri Maoz et al.2025 · 0 citationsPsyArXiv
On the Hardness of Bandit Learning2506.14746v1 · Nataly Brukhim, Aldo Pacchiano, Miroslav Dudik et al.2025 · 0 citationsarXiv
Lexicographic Optimization: Algorithms and Stability2405.01387v1 · Jacob Abernethy, Robert E. Schapire, Umar Syed2024 · 1 citationarXiv
Provable Interactive Learning with Hindsight Instruction Feedback2404.09123v1 · Dipendra Misra, Aldo Pacchiano, Robert E. Schapire2024 · 0 citationsarXiv
A Unified Model and Dimension for Interactive Estimation2306.06184v1 · Nataly Brukhim, Miroslav Dudik, Aldo Pacchiano et al.2023 · 0 citationsarXiv
Provably Sample-Efficient RL with Side Information about Latent Dynamics2205.14237v1 · Yao Liu, Dipendra Misra, Miro Dud'ik et al.2022 · 0 citationsarXiv
Astral Space: Convex Analysis at Infinity2205.03260v4 · Miroslav Dud'ik, Robert E. Schapire, Matus Telgarsky2022 · 0 citationsarXiv
Bayesian decision-making under misspecified priors with applications to meta-learning2107.01509v1 · Max Simchowitz, Christopher Tosh, Akshay Krishnamurthy et al.2021 · 9 citationsarXiv
Interactive Learning from Activity Description2102.07024v2 · Khanh Nguyen, Dipendra Misra, Robert Schapire et al.2021 · 8 citationsarXiv
Gradient descent follows the regularization path for general losses2006.11226v1 · Ziwei Ji, Miroslav Dud'ik, Robert E. Schapire et al.2020 · 14 citationsarXiv
Contextual Search in the Presence of Adversarial Corruptions2002.11650v6 · Akshay Krishnamurthy, Thodoris Lykouris, Chara Podimata et al.2020 · 3 citationsarXiv
Reinforcement Learning with Convex Constraints1906.09323v2 · Sobhan Miryoosefi, Kiant'e Brantley, Hal Daum'e III et al.2019 · 48 citationsAdvances in Neural Information Processing Systems 32 (2019), 14093-14102
Adversarial Bandits with Knapsacks1811.11881v11 · Nicole Immorlica, Karthik Abinav Sankararaman, Robert Schapire et al.2018 · 0 citationsarXiv
Practical Contextual Bandits with Regression Oracles1803.01088v1 · Dylan J. Foster, Alekh Agarwal, Miroslav Dud'ik et al.2018 · 45 citationsarXiv
On Oracle-Efficient PAC RL with Rich Observations1803.00606v4 · Christoph Dann, Nan Jiang, Akshay Krishnamurthy et al.2018 · 25 citationsarXiv
Learning Deep ResNet Blocks Sequentially using Boosting Theory1706.04964v4 · Furong Huang, Jordan Ash, John Langford et al.2017 · 77 citationsarXiv
Corralling a Band of Bandit Algorithms1612.06246v3 · Alekh Agarwal, Haipeng Luo, Behnam Neyshabur et al.2016 · 24 citationsarXiv
Oracle-Efficient Online Learning and Auction Design1611.01688v3 · Miroslav Dud'ik, Nika Haghtalab, Haipeng Luo et al.2016 · 30 citationsarXiv
Contextual Decision Processes with Low Bellman Rank are PAC-Learnable1610.09512v2 · Nan Jiang, Akshay Krishnamurthy, Alekh Agarwal et al.2016 · 144 citationsarXiv
Improved Regret Bounds for Oracle-Based Adversarial Contextual Bandits1606.00313v1 · Vasilis Syrgkanis, Haipeng Luo, Akshay Krishnamurthy et al.2016 · 14 citationsarXiv
Exploratory Gradient Boosting for Reinforcement Learning in Complex Domains1603.04119v1 · David Abel, Alekh Agarwal, Fernando Diaz et al.2016 · 21 citationsarXiv
Unsupervised Domain Adaptation Using Approximate Label Matching1602.04889v3 · Jordan T. Ash, Robert E. Schapire, Barbara E. Engelhardt2016 · 5 citationsarXiv
Efficient Algorithms for Adversarial Contextual Learning1602.02454v1 · Vasilis Syrgkanis, Akshay Krishnamurthy, Robert E. Schapire2016 · 40 citationsarXivon Valency
Functional Frank-Wolfe Boosting for General Loss Functions1510.02558v1 · Chu Wang, Yingfei Wang, Weinan E et al.2015 · 8 citationsarXiv
Fast Convergence of Regularized Learning in Games1507.00407v5 · Vasilis Syrgkanis, Alekh Agarwal, Haipeng Luo et al.2015 · 107 citationsarXivon Valency
Efficient and Parsimonious Agnostic Active Learning1506.08669v3 · Tzu-Kuo Huang, Alekh Agarwal, Daniel J. Hsu et al.2015 · 20 citationsarXiv
Convex Risk Minimization and Conditional Probability Estimation1506.04513v1 · Matus Telgarsky, Miroslav Dud'ik, Robert Schapire2015 · 5 citationsarXiv
Contextual Dueling Bandits1502.06362v2 · Miroslav Dud'ik, Katja Hofmann, Robert E. Schapire et al.2015 · 21 citationsarXiv
Achieving All with No Parameters: Adaptive NormalHedge1502.05934v1 · Haipeng Luo, Robert E. Schapire2015 · 8 citationsarXiv
A Drifting-Games Analysis for Online Learning and Applications to Boosting1406.1856v2 · Haipeng Luo, Robert E. Schapire2014 · 18 citationsarXiv
Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits1402.0555v2 · Alekh Agarwal, Daniel Hsu, Satyen Kale et al.2014 · 286 citationsarXivon Valency
Towards Minimax Online Learning with Unknown Time Horizon1307.8187v2 · Haipeng Luo, Robert E. Schapire2013 · 14 citationsarXiv
Advances in Boosting (Invited Talk)1301.0599v1 · Robert E. Schapire2012 · 1 citationarXiv
A Bayesian Boosting Model1209.1996v1 · Alexander Lorbert, David M. Blei, Robert E. Schapire et al.2012 · 4 citationsarXiv
Imitation Learning with a Value-Based Prior1206.5290v1 · Umar Syed, Robert E. Schapire2012 · 7 citationsarXiv
Combining Spatial and Telemetric Features for Learning Animal Movement Models1203.3486v1 · Berk Kapicioglu, Robert E. Schapire, Martin Wikelski et al.2012 · 1 citationarXiv
Contextual Bandit Learning with Predictable Rewards1202.1334v2 · Alekh Agarwal, Miroslav Dud'ik, Satyen Kale et al.2012 · 43 citationsarXivon Valency
A theory of multiclass boosting1108.2989v1 · Indraneel Mukherjee, Robert E. Schapire2011 · 60 citationsarXiv
The Rate of Convergence of AdaBoost1106.6024v1 · Indraneel Mukherjee, Cynthia Rudin, Robert E. Schapire2011 · 42 citationsarXiv
Decision-Theoretic Bidding Based on Learned Density Models in Simultaneous, Interacting Auctions1106.5270v1 · J. A. Csirik, M. L. Littman, D. McAllester et al.2011 · 66 citationsJournal Of Artificial Intelligence Research, Volume 19, pages 209-242, 2003on Valency
Learning to Order Things1105.5464v1 · W. W. Cohen, R. E. Schapire, Y. Singer2011 · 813 citationsJournal Of Artificial Intelligence Research, Volume 10, pages 243-270, 1999
A Contextual-Bandit Approach to Personalized News Article Recommendation1003.0146v2 · Lihong Li, Wei Chu, John Langford et al.2010 · 2,559 citationsPresented at the Nineteenth International Conference on World Wide Web (WWW 2010), Raleigh, NC, USA, 2010on Valency
Contextual Bandit Algorithms with Supervised Learning Guarantees1002.4058v3 · Alina Beygelzimer, John Langford, Lihong Li et al.2010 · 188 citationsarXivon Valency
Aneuploidy prediction and tumor classification with heterogeneous hidden conditional random fields.19052061 · Barutcuoglu, Zafer, Airoldi, Edoardo M, Dumeaux, Vanessa et al.2009 · 3 citationsBioinformatics (Oxford, England). 2009;25(10):1307-13
Analysis of boosting algorithms using the smooth margin function0803.4092v1 · Cynthia Rudin, Robert E. Schapire, Ingrid Daubechies2008 · 26 citationsAnnals of Statistics 2007, Vol. 35, No. 6, 2723-2768
Faster solutions of the inverse pairwise Ising problem0712.2437v2 · Tamara Broderick, Miroslav Dudik, Gasper Tkacik et al.2007 · 60 citationsarXiv
Hierarchical multi-label prediction of gene function.16410319 · Barutcuoglu, Zafer, Schapire, Robert E, Troyanskaya, Olga G2006 · 491 citationsBioinformatics (Oxford, England). 2006;22(7):830-6
Generalization bounds for averaged classifiersmath/0410092v1 · Yoav Freund, Yishay Mansour, Robert E. Schapire2004 · 43 citationsAnnals of Statistics 2004, Vol. 32, No. 4, 1698-1722
Career total: 339 works. 50 are in this corpus.
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