Robert E. Schapire

ORCID

Publication Activity (10 Years)

Years Active: 1987-2024
Publications (10 Years): 44

Top Venues

Publications

Dipendra Misra, Aldo Pacchiano, Robert E. Schapire
Provable Interactive Learning with Hindsight Instruction Feedback. CoRR (2024)
Jacob D. Abernethy, Robert E. Schapire, Umar Syed
Lexicographic Optimization: Algorithms and Stability. AISTATS (2024)
Akshay Krishnamurthy, Thodoris Lykouris, Chara Podimata, Robert E. Schapire
Contextual Search in the Presence of Adversarial Corruptions. Oper. Res. 71 (4) (2023)
Nataly Brukhim, Miro Dudík, Aldo Pacchiano, Robert E. Schapire
A Unified Model and Dimension for Interactive Estimation. NeurIPS (2023)
Nataly Brukhim, Miroslav Dudík, Aldo Pacchiano, Robert E. Schapire
A Unified Model and Dimension for Interactive Estimation. CoRR (2023)
Yao Liu, Dipendra Misra, Miro Dudík, Robert E. Schapire
Provably Sample-Efficient RL with Side Information about Latent Dynamics. CoRR (2022)
Miroslav Dudík, Ziwei Ji, Robert E. Schapire, Matus Telgarsky
Convex Analysis at Infinity: An Introduction to Astral Space. CoRR (2022)
Nicole Immorlica, Karthik Abinav Sankararaman, Robert E. Schapire, Aleksandrs Slivkins
Adversarial Bandits with Knapsacks. J. ACM 69 (6) (2022)
Yao Liu, Dipendra Misra, Miro Dudík, Robert E. Schapire
Provably sample-efficient RL with side information about latent dynamics. NeurIPS (2022)
Max Simchowitz, Christopher Tosh, Akshay Krishnamurthy, Daniel J. Hsu, Thodoris Lykouris, Miroslav Dudík, Robert E. Schapire
Bayesian decision-making under misspecified priors with applications to meta-learning. NeurIPS (2021)
Khanh Nguyen, Dipendra Misra, Robert E. Schapire, Miroslav Dudík, Patrick Shafto
Interactive Learning from Activity Description. ICML (2021)
Akshay Krishnamurthy, Thodoris Lykouris, Chara Podimata, Robert E. Schapire
Contextual search in the presence of irrational agents. STOC (2021)
Nataly Brukhim, Elad Hazan, Shay Moran, Indraneel Mukherjee, Robert E. Schapire
Multiclass Boosting and the Cost of Weak Learning. NeurIPS (2021)
Max Simchowitz, Christopher Tosh, Akshay Krishnamurthy, Daniel Hsu, Thodoris Lykouris, Miroslav Dudík, Robert E. Schapire
Bayesian decision-making under misspecified priors with applications to meta-learning. CoRR (2021)
Khanh Nguyen, Dipendra Misra, Robert E. Schapire, Miroslav Dudík, Patrick Shafto
Interactive Learning from Activity Description. CoRR (2021)
Ziwei Ji, Miroslav Dudík, Robert E. Schapire, Matus Telgarsky
Gradient descent follows the regularization path for general losses. COLT (2020)
Miroslav Dudíte, Nika Haghtalab, Haipeng Luo, Robert E. Schapire, Vasilis Syrgkanis, Jennifer Wortman Vaughan
Oracle-efficient Online Learning and Auction Design. J. ACM 67 (5) (2020)
Ziwei Ji, Miroslav Dudík, Robert E. Schapire, Matus Telgarsky
Gradient descent follows the regularization path for general losses. CoRR (2020)
Ehsan Emamjomeh-Zadeh, David Kempe, Mohammad Mahdian, Robert E. Schapire
Interactive Learning of a Dynamic Structure. ALT (2020)
Nicole Immorlica, Karthik Abinav Sankararaman, Robert E. Schapire, Aleksandrs Slivkins
Adversarial Bandits with Knapsacks. FOCS (2019)
Sobhan Miryoosefi, Kianté Brantley, Hal Daumé III, Miroslav Dudík, Robert E. Schapire
Reinforcement Learning with Convex Constraints. NeurIPS (2019)
Sobhan Miryoosefi, Kianté Brantley, Hal Daumé III, Miroslav Dudík, Robert E. Schapire
Reinforcement Learning with Convex Constraints. CoRR (2019)
Furong Huang, Jordan T. Ash, John Langford, Robert E. Schapire
Learning Deep ResNet Blocks Sequentially using Boosting Theory. ICML (2018)
Christoph Dann, Nan Jiang, Akshay Krishnamurthy, Alekh Agarwal, John Langford, Robert E. Schapire
On Oracle-Efficient PAC RL with Rich Observations. NeurIPS (2018)
Dylan J. Foster, Alekh Agarwal, Miroslav Dudík, Haipeng Luo, Robert E. Schapire
Practical Contextual Bandits with Regression Oracles. ICML (2018)
Christoph Dann, Nan Jiang, Akshay Krishnamurthy, Alekh Agarwal, John Langford, Robert E. Schapire
On Polynomial Time PAC Reinforcement Learning with Rich Observations. CoRR (2018)
Uriel Feige, Yishay Mansour, Robert E. Schapire
Robust Inference for Multiclass Classification. ALT (2018)
Nicole Immorlica, Karthik Abinav Sankararaman, Robert E. Schapire, Aleksandrs Slivkins
Adversarial Bandits with Knapsacks. CoRR (2018)
Dylan J. Foster, Alekh Agarwal, Miroslav Dudík, Haipeng Luo, Robert E. Schapire
Practical Contextual Bandits with Regression Oracles. CoRR (2018)
Nan Jiang, Akshay Krishnamurthy, Alekh Agarwal, John Langford, Robert E. Schapire
Contextual Decision Processes with low Bellman rank are PAC-Learnable. ICML (2017)
Alekh Agarwal, Akshay Krishnamurthy, John Langford, Haipeng Luo, Robert E. Schapire
Open Problem: First-Order Regret Bounds for Contextual Bandits. COLT (2017)
Miroslav Dudík, Nika Haghtalab, Haipeng Luo, Robert E. Schapire, Vasilis Syrgkanis, Jennifer Wortman Vaughan
Oracle-Efficient Online Learning and Auction Design. FOCS (2017)
Furong Huang, Jordan T. Ash, John Langford, Robert E. Schapire
Learning Deep ResNet Blocks Sequentially using Boosting Theory. CoRR (2017)
Alekh Agarwal, Haipeng Luo, Behnam Neyshabur, Robert E. Schapire
Corralling a Band of Bandit Algorithms. COLT (2017)
Vasilis Syrgkanis, Haipeng Luo, Akshay Krishnamurthy, Robert E. Schapire
Improved Regret Bounds for Oracle-Based Adversarial Contextual Bandits. CoRR (2016)
Akshay Balsubramani, Zohar S. Karnin, Robert E. Schapire, Masrour Zoghi
Instance-dependent Regret Bounds for Dueling Bandits. COLT (2016)
Jordan T. Ash, Robert E. Schapire
Multi-Source Domain Adaptation Using Approximate Label Matching. CoRR (2016)
Miroslav Dudík, Nika Haghtalab, Haipeng Luo, Robert E. Schapire, Vasilis Syrgkanis, Jennifer Wortman Vaughan
Oracle-Efficient Learning and Auction Design. CoRR (2016)
David Abel, Alekh Agarwal, Fernando Diaz, Akshay Krishnamurthy, Robert E. Schapire
Exploratory Gradient Boosting for Reinforcement Learning in Complex Domains. CoRR (2016)
Vasilis Syrgkanis, Haipeng Luo, Akshay Krishnamurthy, Robert E. Schapire
Improved Regret Bounds for Oracle-Based Adversarial Contextual Bandits. NIPS (2016)
Vasilis Syrgkanis, Akshay Krishnamurthy, Robert E. Schapire
Efficient Algorithms for Adversarial Contextual Learning. ICML (2016)
Nan Jiang, Akshay Krishnamurthy, Alekh Agarwal, John Langford, Robert E. Schapire
Contextual Decision Processes with Low Bellman Rank are PAC-Learnable. CoRR (2016)
Vasilis Syrgkanis, Akshay Krishnamurthy, Robert E. Schapire
Efficient Algorithms for Adversarial Contextual Learning. CoRR (2016)
Alekh Agarwal, Haipeng Luo, Behnam Neyshabur, Robert E. Schapire
Corralling a Band of Bandit Algorithms. CoRR (2016)
Tzu-Kuo Huang, Alekh Agarwal, Daniel J. Hsu, John Langford, Robert E. Schapire
Efficient and Parsimonious Agnostic Active Learning. NIPS (2015)
Matus Telgarsky, Miroslav Dudík, Robert E. Schapire
Convex Risk Minimization and Conditional Probability Estimation. CoRR (2015)
Haipeng Luo, Robert E. Schapire
Achieving All with No Parameters: AdaNormalHedge. COLT (2015)
Zhuo Wang, Robert E. Schapire, Naveen Verma
Error Adaptive Classifier Boosting (EACB): Leveraging Data-Driven Training Towards Hardware Resilience for Signal Inference. IEEE Trans. Circuits Syst. I Regul. Pap. (4) (2015)
Uriel Feige, Yishay Mansour, Robert E. Schapire
Learning and inference in the presence of corrupted inputs. COLT (2015)
Tzu-Kuo Huang, Alekh Agarwal, Daniel J. Hsu, John Langford, Robert E. Schapire
Efficient and Parsimonious Agnostic Active Learning. CoRR (2015)
Miroslav Dudík, Katja Hofmann, Robert E. Schapire, Aleksandrs Slivkins, Masrour Zoghi
Contextual Dueling Bandits. CoRR (2015)
Chu Wang, Yingfei Wang, Weinan E, Robert E. Schapire
Functional Frank-Wolfe Boosting for General Loss Functions. CoRR (2015)
Miroslav Dudík, Katja Hofmann, Robert E. Schapire, Aleksandrs Slivkins, Masrour Zoghi
Contextual Dueling Bandits. COLT (2015)
Vasilis Syrgkanis, Alekh Agarwal, Haipeng Luo, Robert E. Schapire
Fast Convergence of Regularized Learning in Games. CoRR (2015)
Vasilis Syrgkanis, Alekh Agarwal, Haipeng Luo, Robert E. Schapire
Fast Convergence of Regularized Learning in Games. NIPS (2015)
Berk Kapicioglu, David S. Rosenberg, Robert E. Schapire, Tony Jebara
Collaborative Place Models. IJCAI (2015)
Haipeng Luo, Robert E. Schapire
Achieving All with No Parameters: Adaptive NormalHedge. CoRR (2015)
Aurelie C. Lozano, Sanjeev R. Kulkarni, Robert E. Schapire
Convergence and Consistency of Regularized Boosting With Weakly Dependent Observations. IEEE Trans. Inf. Theory 60 (1) (2014)
Haipeng Luo, Robert E. Schapire
A Drifting-Games Analysis for Online Learning and Applications to Boosting. CoRR (2014)
Haipeng Luo, Robert E. Schapire
A Drifting-Games Analysis for Online Learning and Applications to Boosting. NIPS (2014)
Zhuo Wang, Robert E. Schapire, Naveen Verma
Error-adaptive classifier boosting (EACB): Exploiting data-driven training for highly fault-tolerant hardware. ICASSP (2014)
Haipeng Luo, Robert E. Schapire
Towards Minimax Online Learning with Unknown Time Horizon. ICML (2014)
Berk Kapicioglu, David S. Rosenberg, Robert E. Schapire, Tony Jebara
Collaborative Ranking for Local Preferences. AISTATS (2014)
Alekh Agarwal, Daniel J. Hsu, Satyen Kale, John Langford, Lihong Li, Robert E. Schapire
Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits. CoRR (2014)
Alekh Agarwal, Daniel J. Hsu, Satyen Kale, John Langford, Lihong Li, Robert E. Schapire
Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits. ICML (2014)
Alekh Agarwal, Ashwinkumar Badanidiyuru, Miroslav Dudík, Robert E. Schapire, Aleksandrs Slivkins
Robust Multi-objective Learning with Mentor Feedback. COLT (2014)
Robert E. Schapire
Advances in Boosting (Invited Talk) CoRR (2013)
Haipeng Luo, Robert E. Schapire
Online Learning with Unknown Time Horizon. CoRR (2013)
Robert E. Schapire
Explaining AdaBoost. Empirical Inference (2013)
Indraneel Mukherjee, Cynthia Rudin, Robert E. Schapire
The rate of convergence of AdaBoost. J. Mach. Learn. Res. 14 (1) (2013)
Indraneel Mukherjee, Robert E. Schapire
A theory of multiclass boosting. J. Mach. Learn. Res. 14 (1) (2013)
Umar Syed, Robert E. Schapire
Imitation Learning with a Value-Based Prior CoRR (2012)
Berk Kapicioglu, Robert E. Schapire, Martin Wikelski, Tamara Broderick
Combining Spatial and Telemetric Features for Learning Animal Movement Models CoRR (2012)
Alekh Agarwal, Miroslav Dudík, Satyen Kale, John Langford, Robert E. Schapire
Contextual Bandit Learning with Predictable Rewards. AISTATS (2012)
Cynthia Rudin, Robert E. Schapire, Ingrid Daubechies
Open Problem: Does AdaBoost Always Cycle? COLT (2012)
Alekh Agarwal, Miroslav Dudík, Satyen Kale, John Langford, Robert E. Schapire
Contextual Bandit Learning with Predictable Rewards CoRR (2012)
Sina Jafarpour, Robert E. Schapire, Volkan Cevher
Compressive sensing meets game theory. ICASSP (2011)
Sina Jafarpour, Volkan Cevher, Robert E. Schapire
A game theoretic approach to expander-based compressive sensing. ISIT (2011)
Indraneel Mukherjee, Cynthia Rudin, Robert E. Schapire
The Rate of Convergence of Adaboost. COLT (2011)
Alina Beygelzimer, John Langford, Lihong Li, Lev Reyzin, Robert E. Schapire
Contextual Bandit Algorithms with Supervised Learning Guarantees. AISTATS (2011)
Indraneel Mukherjee, Robert E. Schapire
A theory of multiclass boosting CoRR (2011)
Indraneel Mukherjee, Cynthia Rudin, Robert E. Schapire
The Rate of Convergence of AdaBoost CoRR (2011)
William W. Cohen, Robert E. Schapire, Yoram Singer
Learning to Order Things CoRR (2011)
Wei Chu, Lihong Li, Lev Reyzin, Robert E. Schapire
Contextual Bandits with Linear Payoff Functions. AISTATS (2011)
János A. Csirik, Michael L. Littman, David A. McAllester, Robert E. Schapire, Peter Stone
Decision-Theoretic Bidding Based on Learned Density Models in Simultaneous, Interacting Auctions CoRR (2011)
Satyen Kale, Lev Reyzin, Robert E. Schapire
Non-Stochastic Bandit Slate Problems. NIPS (2010)
Lihong Li, Wei Chu, John Langford, Robert E. Schapire
A contextual-bandit approach to personalized news article recommendation. WWW (2010)
Lihong Li, Wei Chu, John Langford, Robert E. Schapire
A Contextual-Bandit Approach to Personalized News Article Recommendation CoRR (2010)
Indraneel Mukherjee, Robert E. Schapire
Learning with continuous experts using drifting games. Theor. Comput. Sci. 411 (29-30) (2010)
Alina Beygelzimer, John Langford, Lihong Li, Lev Reyzin, Robert E. Schapire
An Optimal High Probability Algorithm for the Contextual Bandit Problem CoRR (2010)
Robert E. Schapire
The Convergence Rate of AdaBoost. COLT (2010)
Umar Syed, Robert E. Schapire
A Reduction from Apprenticeship Learning to Classification. NIPS (2010)
Berk Kapicioglu, Robert E. Schapire, Martin Wikelski, Tamara Broderick
Combining Spatial and Telemetric Features for Learning Animal Movement Models. UAI (2010)
Indraneel Mukherjee, Robert E. Schapire
A Theory of Multiclass Boosting. NIPS (2010)
Yongxin Taylor Xi, Zhen James Xiang, Peter J. Ramadge, Robert E. Schapire
Speed and Sparsity of Regularized Boosting. AISTATS (2009)
Zafer Barutçuoglu, Edoardo M. Airoldi, Vanessa Dumeaux, Robert E. Schapire, Olga G. Troyanskaya
Aneuploidy prediction and tumor classification with heterogeneous hidden conditional random fields. Bioinform. 25 (10) (2009)
Cynthia Rudin, Robert E. Schapire
Margin-based Ranking and an Equivalence between AdaBoost and RankBoost. J. Mach. Learn. Res. 10 (2009)
Indraneel Mukherjee, Robert E. Schapire
Learning with Continuous Experts Using Drifting Games. ALT (2008)
Ioannis C. Avramopoulos, Jennifer Rexford, Robert E. Schapire
From Optimization to Regret Minimization and Back Again. SysML (2008)
Chris Bourke, Kun Deng, Stephen D. Scott, Robert E. Schapire, N. V. Vinodchandran
On reoptimizing multi-class classifiers. Mach. Learn. 71 (2-3) (2008)

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Publication Activity (10 Years)

Top Topics

Top Venues

Robert E. Schapire