Robert E. Schapire

213 papers A* 82A 13B 5Misc 3Journal 86Unranked 23

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Learning to Reason with Curriculum I: Provable Benefits of Autocurriculum. CoRR Nived Rajaraman, Audrey Huang, Miroslav Dudík, Robert E. Schapire, Dylan J. Foster, Akshay Krishnamurthy
2025	A*	`conf`	On the Hardness of Bandit Learning. COLT Nataly Brukhim, Aldo Pacchiano, Miroslav Dudík, Robert E. Schapire
2025	J	`jnl`	On the Hardness of Bandit Learning. CoRR Nataly Brukhim, Aldo Pacchiano, Miroslav Dudík, Robert E. Schapire
2024	A	`conf`	Lexicographic Optimization: Algorithms and Stability. AISTATS Jacob D. Abernethy, Robert E. Schapire, Umar Syed
2024	A*	`conf`	Provable Interactive Learning with Hindsight Instruction Feedback. ICML Dipendra Misra, Aldo Pacchiano, Robert E. Schapire
2024	J	`jnl`	Provable Interactive Learning with Hindsight Instruction Feedback. CoRR Dipendra Misra, Aldo Pacchiano, Robert E. Schapire
2023	A*	`conf`	A Unified Model and Dimension for Interactive Estimation. NeurIPS Nataly Brukhim, Miro Dudík, Aldo Pacchiano, Robert E. Schapire
2023	J	`jnl`	A Unified Model and Dimension for Interactive Estimation. CoRR Nataly Brukhim, Miroslav Dudík, Aldo Pacchiano, Robert E. Schapire
2023	J	`jnl`	Contextual Search in the Presence of Adversarial Corruptions. Oper. Res. Akshay Krishnamurthy, Thodoris Lykouris, Chara Podimata, Robert E. Schapire
2022	J	`jnl`	Adversarial Bandits with Knapsacks. J. ACM Nicole Immorlica, Karthik Abinav Sankararaman, Robert E. Schapire, Aleksandrs Slivkins
2022	J	`jnl`	Convex Analysis at Infinity: An Introduction to Astral Space. CoRR Miroslav Dudík, Ziwei Ji, Robert E. Schapire, Matus Telgarsky
2022	J	`jnl`	Provably Sample-Efficient RL with Side Information about Latent Dynamics. CoRR Yao Liu, Dipendra Misra, Miro Dudík, Robert E. Schapire
2022	A*	`conf`	Provably sample-efficient RL with side information about latent dynamics. NeurIPS Yao Liu, Dipendra Misra, Miro Dudík, Robert E. Schapire
2021	A*	`conf`	Bayesian decision-making under misspecified priors with applications to meta-learning. NeurIPS Max Simchowitz, Christopher Tosh, Akshay Krishnamurthy, Daniel J. Hsu, Thodoris Lykouris, Miroslav Dudík, Robert E. Schapire
2021	J	`jnl`	Bayesian decision-making under misspecified priors with applications to meta-learning. CoRR Max Simchowitz, Christopher Tosh, Akshay Krishnamurthy, Daniel Hsu, Thodoris Lykouris, Miroslav Dudík, Robert E. Schapire
2021	A*	`conf`	Contextual search in the presence of irrational agents. STOC Akshay Krishnamurthy, Thodoris Lykouris, Chara Podimata, Robert E. Schapire
2021	A*	`conf`	Interactive Learning from Activity Description. ICML Khanh Nguyen, Dipendra Misra, Robert E. Schapire, Miroslav Dudík, Patrick Shafto
2021	J	`jnl`	Interactive Learning from Activity Description. CoRR Khanh Nguyen, Dipendra Misra, Robert E. Schapire, Miroslav Dudík, Patrick Shafto
2021	A*	`conf`	Multiclass Boosting and the Cost of Weak Learning. NeurIPS Nataly Brukhim, Elad Hazan, Shay Moran, Indraneel Mukherjee, Robert E. Schapire
2020	A*	`conf`	Gradient descent follows the regularization path for general losses. COLT Ziwei Ji, Miroslav Dudík, Robert E. Schapire, Matus Telgarsky
2020	J	`jnl`	Gradient descent follows the regularization path for general losses. CoRR Ziwei Ji, Miroslav Dudík, Robert E. Schapire, Matus Telgarsky
2020	B	`conf`	Interactive Learning of a Dynamic Structure. ALT Ehsan Emamjomeh-Zadeh, David Kempe, Mohammad Mahdian, Robert E. Schapire
2020	J	`jnl`	Oracle-efficient Online Learning and Auction Design. J. ACM Miroslav Dudík, Nika Haghtalab, Haipeng Luo, Robert E. Schapire, Vasilis Syrgkanis, Jennifer Wortman Vaughan
2019	A*	`conf`	Adversarial Bandits with Knapsacks. FOCS Nicole Immorlica, Karthik Abinav Sankararaman, Robert E. Schapire, Aleksandrs Slivkins
2019	A*	`conf`	Reinforcement Learning with Convex Constraints. NeurIPS Sobhan Miryoosefi, Kianté Brantley, Hal Daumé III, Miroslav Dudík, Robert E. Schapire
2019	J	`jnl`	Reinforcement Learning with Convex Constraints. CoRR Sobhan Miryoosefi, Kianté Brantley, Hal Daumé III, Miroslav Dudík, Robert E. Schapire
2018	J	`jnl`	Adversarial Bandits with Knapsacks. CoRR Nicole Immorlica, Karthik Abinav Sankararaman, Robert E. Schapire, Aleksandrs Slivkins
2018	A*	`conf`	Learning Deep ResNet Blocks Sequentially using Boosting Theory. ICML Furong Huang, Jordan T. Ash, John Langford, Robert E. Schapire
2018	A*	`conf`	On Oracle-Efficient PAC RL with Rich Observations. NeurIPS Christoph Dann, Nan Jiang, Akshay Krishnamurthy, Alekh Agarwal, John Langford, Robert E. Schapire
2018	J	`jnl`	On Polynomial Time PAC Reinforcement Learning with Rich Observations. CoRR Christoph Dann, Nan Jiang, Akshay Krishnamurthy, Alekh Agarwal, John Langford, Robert E. Schapire
2018	A*	`conf`	Practical Contextual Bandits with Regression Oracles. ICML Dylan J. Foster, Alekh Agarwal, Miroslav Dudík, Haipeng Luo, Robert E. Schapire
2018	J	`jnl`	Practical Contextual Bandits with Regression Oracles. CoRR Dylan J. Foster, Alekh Agarwal, Miroslav Dudík, Haipeng Luo, Robert E. Schapire
2018	B	`conf`	Robust Inference for Multiclass Classification. ALT Uriel Feige, Yishay Mansour, Robert E. Schapire
2017	A*	`conf`	Contextual Decision Processes with low Bellman rank are PAC-Learnable. ICML Nan Jiang, Akshay Krishnamurthy, Alekh Agarwal, John Langford, Robert E. Schapire
2017	A*	`conf`	Corralling a Band of Bandit Algorithms. COLT Alekh Agarwal, Haipeng Luo, Behnam Neyshabur, Robert E. Schapire
2017	J	`jnl`	Learning Deep ResNet Blocks Sequentially using Boosting Theory. CoRR Furong Huang, Jordan T. Ash, John Langford, Robert E. Schapire
2017	A*	`conf`	Open Problem: First-Order Regret Bounds for Contextual Bandits. COLT Alekh Agarwal, Akshay Krishnamurthy, John Langford, Haipeng Luo, Robert E. Schapire
2017	A*	`conf`	Oracle-Efficient Online Learning and Auction Design. FOCS Miroslav Dudík, Nika Haghtalab, Haipeng Luo, Robert E. Schapire, Vasilis Syrgkanis, Jennifer Wortman Vaughan
2016	J	`jnl`	Contextual Decision Processes with Low Bellman Rank are PAC-Learnable. CoRR Nan Jiang, Akshay Krishnamurthy, Alekh Agarwal, John Langford, Robert E. Schapire
2016	J	`jnl`	Corralling a Band of Bandit Algorithms. CoRR Alekh Agarwal, Haipeng Luo, Behnam Neyshabur, Robert E. Schapire
2016	A*	`conf`	Efficient Algorithms for Adversarial Contextual Learning. ICML Vasilis Syrgkanis, Akshay Krishnamurthy, Robert E. Schapire
2016	J	`jnl`	Efficient Algorithms for Adversarial Contextual Learning. CoRR Vasilis Syrgkanis, Akshay Krishnamurthy, Robert E. Schapire
2016	J	`jnl`	Exploratory Gradient Boosting for Reinforcement Learning in Complex Domains. CoRR David Abel, Alekh Agarwal, Fernando Diaz, Akshay Krishnamurthy, Robert E. Schapire
2016	—	`conf`	Improved Regret Bounds for Oracle-Based Adversarial Contextual Bandits. NIPS Vasilis Syrgkanis, Haipeng Luo, Akshay Krishnamurthy, Robert E. Schapire
2016	J	`jnl`	Improved Regret Bounds for Oracle-Based Adversarial Contextual Bandits. CoRR Vasilis Syrgkanis, Haipeng Luo, Akshay Krishnamurthy, Robert E. Schapire
2016	A*	`conf`	Instance-dependent Regret Bounds for Dueling Bandits. COLT Akshay Balsubramani, Zohar S. Karnin, Robert E. Schapire, Masrour Zoghi
2016	J	`jnl`	Multi-Source Domain Adaptation Using Approximate Label Matching. CoRR Jordan T. Ash, Robert E. Schapire
2016	J	`jnl`	Oracle-Efficient Learning and Auction Design. CoRR Miroslav Dudík, Nika Haghtalab, Haipeng Luo, Robert E. Schapire, Vasilis Syrgkanis, Jennifer Wortman Vaughan
2015	A*	`conf`	Achieving All with No Parameters: AdaNormalHedge. COLT Haipeng Luo, Robert E. Schapire
2015	J	`jnl`	Achieving All with No Parameters: Adaptive NormalHedge. CoRR Haipeng Luo, Robert E. Schapire
2015	A*	`conf`	Collaborative Place Models. IJCAI Berk Kapicioglu, David S. Rosenberg, Robert E. Schapire, Tony Jebara
2015	A*	`conf`	Contextual Dueling Bandits. COLT Miroslav Dudík, Katja Hofmann, Robert E. Schapire, Aleksandrs Slivkins, Masrour Zoghi
2015	J	`jnl`	Contextual Dueling Bandits. CoRR Miroslav Dudík, Katja Hofmann, Robert E. Schapire, Aleksandrs Slivkins, Masrour Zoghi
2015	J	`jnl`	Convex Risk Minimization and Conditional Probability Estimation. CoRR Matus Telgarsky, Miroslav Dudík, Robert E. Schapire
2015	—	`conf`	Efficient and Parsimonious Agnostic Active Learning. NIPS Tzu-Kuo Huang, Alekh Agarwal, Daniel J. Hsu, John Langford, Robert E. Schapire
2015	J	`jnl`	Efficient and Parsimonious Agnostic Active Learning. CoRR Tzu-Kuo Huang, Alekh Agarwal, Daniel J. Hsu, John Langford, Robert E. Schapire
2015	J	`jnl`	Error Adaptive Classifier Boosting (EACB): Leveraging Data-Driven Training Towards Hardware Resilience for Signal Inference. IEEE Trans. Circuits Syst. I Regul. Pap. Zhuo Wang, Robert E. Schapire, Naveen Verma
2015	—	`conf`	Fast Convergence of Regularized Learning in Games. NIPS Vasilis Syrgkanis, Alekh Agarwal, Haipeng Luo, Robert E. Schapire
2015	J	`jnl`	Fast Convergence of Regularized Learning in Games. CoRR Vasilis Syrgkanis, Alekh Agarwal, Haipeng Luo, Robert E. Schapire
2015	J	`jnl`	Functional Frank-Wolfe Boosting for General Loss Functions. CoRR Chu Wang, Yingfei Wang, Weinan E, Robert E. Schapire
2015	A*	`conf`	Learning and inference in the presence of corrupted inputs. COLT Uriel Feige, Yishay Mansour, Robert E. Schapire
2014	—	`conf`	A Drifting-Games Analysis for Online Learning and Applications to Boosting. NIPS Haipeng Luo, Robert E. Schapire
2014	J	`jnl`	A Drifting-Games Analysis for Online Learning and Applications to Boosting. CoRR Haipeng Luo, Robert E. Schapire
2014	A	`conf`	Collaborative Ranking for Local Preferences. AISTATS Berk Kapicioglu, David S. Rosenberg, Robert E. Schapire, Tony Jebara
2014	J	`jnl`	Convergence and Consistency of Regularized Boosting With Weakly Dependent Observations. IEEE Trans. Inf. Theory Aurélie C. Lozano, Sanjeev R. Kulkarni, Robert E. Schapire
2014	Misc	`conf`	Error-adaptive classifier boosting (EACB): Exploiting data-driven training for highly fault-tolerant hardware. ICASSP Zhuo Wang, Robert E. Schapire, Naveen Verma
2014	A*	`conf`	Robust Multi-objective Learning with Mentor Feedback. COLT Alekh Agarwal, Ashwinkumar Badanidiyuru, Miroslav Dudík, Robert E. Schapire, Aleksandrs Slivkins
2014	A*	`conf`	Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits. ICML Alekh Agarwal, Daniel J. Hsu, Satyen Kale, John Langford, Lihong Li, Robert E. Schapire
2014	J	`jnl`	Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits. CoRR Alekh Agarwal, Daniel J. Hsu, Satyen Kale, John Langford, Lihong Li, Robert E. Schapire
2014	A*	`conf`	Towards Minimax Online Learning with Unknown Time Horizon. ICML Haipeng Luo, Robert E. Schapire
2013	J	`jnl`	A theory of multiclass boosting. J. Mach. Learn. Res. Indraneel Mukherjee, Robert E. Schapire
2013	J	`jnl`	Advances in Boosting (Invited Talk) CoRR Robert E. Schapire
2013	—	`conf`	Explaining AdaBoost. Empirical Inference Robert E. Schapire
2013	J	`jnl`	Online Learning with Unknown Time Horizon. CoRR Haipeng Luo, Robert E. Schapire
2013	J	`jnl`	The rate of convergence of AdaBoost. J. Mach. Learn. Res. Indraneel Mukherjee, Cynthia Rudin, Robert E. Schapire
2012	J	`jnl`	Combining Spatial and Telemetric Features for Learning Animal Movement Models CoRR Berk Kapicioglu, Robert E. Schapire, Martin Wikelski, Tamara Broderick
2012	J	`jnl`	Contextual Bandit Learning with Predictable Rewards CoRR Alekh Agarwal, Miroslav Dudík, Satyen Kale, John Langford, Robert E. Schapire
2012	A	`conf`	Contextual Bandit Learning with Predictable Rewards. AISTATS Alekh Agarwal, Miroslav Dudík, Satyen Kale, John Langford, Robert E. Schapire
2012	J	`jnl`	Imitation Learning with a Value-Based Prior CoRR Umar Syed, Robert E. Schapire
2012	A*	`conf`	Open Problem: Does AdaBoost Always Cycle? COLT Cynthia Rudin, Robert E. Schapire, Ingrid Daubechies
2011	B	`conf`	A game theoretic approach to expander-based compressive sensing. ISIT Sina Jafarpour, Volkan Cevher, Robert E. Schapire
2011	J	`jnl`	A theory of multiclass boosting CoRR Indraneel Mukherjee, Robert E. Schapire
2011	Misc	`conf`	Compressive sensing meets game theory. ICASSP Sina Jafarpour, Robert E. Schapire, Volkan Cevher
2011	A	`conf`	Contextual Bandit Algorithms with Supervised Learning Guarantees. AISTATS Alina Beygelzimer, John Langford, Lihong Li, Lev Reyzin, Robert E. Schapire
2011	A	`conf`	Contextual Bandits with Linear Payoff Functions. AISTATS Wei Chu, Lihong Li, Lev Reyzin, Robert E. Schapire
2011	J	`jnl`	Decision-Theoretic Bidding Based on Learned Density Models in Simultaneous, Interacting Auctions CoRR János A. Csirik, Michael L. Littman, David A. McAllester, Robert E. Schapire, Peter Stone
2011	J	`jnl`	Learning to Order Things CoRR William W. Cohen, Robert E. Schapire, Yoram Singer
2011	J	`jnl`	The Rate of Convergence of AdaBoost CoRR Indraneel Mukherjee, Cynthia Rudin, Robert E. Schapire
2011	A*	`conf`	The Rate of Convergence of Adaboost. COLT Indraneel Mukherjee, Cynthia Rudin, Robert E. Schapire
2010	J	`jnl`	A Contextual-Bandit Approach to Personalized News Article Recommendation CoRR Lihong Li, Wei Chu, John Langford, Robert E. Schapire
2010	—	`conf`	A Reduction from Apprenticeship Learning to Classification. NIPS Umar Syed, Robert E. Schapire
2010	—	`conf`	A Theory of Multiclass Boosting. NIPS Indraneel Mukherjee, Robert E. Schapire
2010	A*	`conf`	A contextual-bandit approach to personalized news article recommendation. WWW Lihong Li, Wei Chu, John Langford, Robert E. Schapire
2010	J	`jnl`	An Optimal High Probability Algorithm for the Contextual Bandit Problem CoRR Alina Beygelzimer, John Langford, Lihong Li, Lev Reyzin, Robert E. Schapire
2010	A	`conf`	Combining Spatial and Telemetric Features for Learning Animal Movement Models. UAI Berk Kapicioglu, Robert E. Schapire, Martin Wikelski, Tamara Broderick
2010	J	`jnl`	Learning with continuous experts using drifting games. Theor. Comput. Sci. Indraneel Mukherjee, Robert E. Schapire
2010	—	`conf`	Non-Stochastic Bandit Slate Problems. NIPS Satyen Kale, Lev Reyzin, Robert E. Schapire
2010	A*	`conf`	The Convergence Rate of AdaBoost. COLT Robert E. Schapire
2009	J	`jnl`	Aneuploidy prediction and tumor classification with heterogeneous hidden conditional random fields. Bioinform. Zafer Barutçuoglu, Edoardo M. Airoldi, Vanessa Dumeaux, Robert E. Schapire, Olga G. Troyanskaya
2009	J	`jnl`	Margin-based Ranking and an Equivalence between AdaBoost and RankBoost. J. Mach. Learn. Res. Cynthia Rudin, Robert E. Schapire
2009	A	`conf`	Speed and Sparsity of Regularized Boosting. AISTATS Yongxin Taylor Xi, Zhen James Xiang, Peter J. Ramadge, Robert E. Schapire
2008	A*	`conf`	Apprenticeship learning using linear programming. ICML Umar Syed, Michael H. Bowling, Robert E. Schapire
2008	—	`conf`	From Optimization to Regret Minimization and Back Again. SysML Ioannis C. Avramopoulos, Jennifer Rexford, Robert E. Schapire
2008	B	`conf`	Learning with Continuous Experts Using Drifting Games. ALT Indraneel Mukherjee, Robert E. Schapire
2008	J	`jnl`	On reoptimizing multi-class classifiers. Mach. Learn. Chris Bourke, Kun Deng, Stephen D. Scott, Robert E. Schapire, N. V. Vinodchandran
2007	—	`conf`	A Game-Theoretic Approach to Apprenticeship Learning. NIPS Umar Syed, Robert E. Schapire
2007	—	`conf`	FilterBoost: Regression and Classification on Large Datasets. NIPS Joseph K. Bradley, Robert E. Schapire
2007	A*	`conf`	Hierarchical maximum entropy density estimation. ICML Miroslav Dudík, David M. Blei, Robert E. Schapire
2007	A	`conf`	Imitation Learning with a Value-Based Prior. UAI Umar Syed, Robert E. Schapire
2007	A	`conf`	Maximum Entropy Correlated Equilibria. AISTATS Luis E. Ortiz, Robert E. Schapire, Sham M. Kakade
2007	J	`jnl`	Maximum Entropy Density Estimation with Generalized Regularization and an Application to Species Distribution Modeling. J. Mach. Learn. Res. Miroslav Dudík, Steven J. Phillips, Robert E. Schapire
2006	A*	`conf`	Algorithms for portfolio management based on the Newton method. ICML Amit Agarwal, Elad Hazan, Satyen Kale, Robert E. Schapire
2006	J	`jnl`	Hierarchical multi-label prediction of gene function. Bioinform. Zafer Barutçuoglu, Robert E. Schapire, Olga G. Troyanskaya
2006	A*	`conf`	How boosting the margin can also boost classifier complexity. ICML Lev Reyzin, Robert E. Schapire
2006	A*	`conf`	Maximum Entropy Distribution Estimation with Generalized Regularization. COLT Miroslav Dudík, Robert E. Schapire
2005	J	`jnl`	Boosting with prior knowledge for call classification. IEEE Trans. Speech Audio Process. Robert E. Schapire, Marie Rochery, Mazin G. Rahim, Narendra K. Gupta
2005	J	`jnl`	Combining active and semi-supervised learning for spoken language understanding. Speech Commun. Gökhan Tür, Dilek Hakkani-Tür, Robert E. Schapire
2005	—	`conf`	Convergence and Consistency of Regularized Boosting Algorithms with Stationary B-Mixing Observations. NIPS Aurélie C. Lozano, Sanjeev R. Kulkarni, Robert E. Schapire
2005	—	`conf`	Correcting sample selection bias in maximum entropy density estimation. NIPS Miroslav Dudík, Robert E. Schapire, Steven J. Phillips
2005	J	`jnl`	Efficient Multiclass Implementations of L1-Regularized Maximum Entropy CoRR Patrick Haffner, Steven J. Phillips, Robert E. Schapire
2005	A*	`conf`	Margin-Based Ranking Meets Boosting in the Middle. COLT Cynthia Rudin, Corinna Cortes, Mehryar Mohri, Robert E. Schapire
2004	A*	`conf`	A maximum entropy approach to species distribution modeling. ICML Steven J. Phillips, Miroslav Dudík, Robert E. Schapire
2004	A*	`conf`	Boosting Based on a Smooth Margin. COLT Cynthia Rudin, Robert E. Schapire, Ingrid Daubechies
2004	A*	`conf`	Performance Guarantees for Regularized Maximum Entropy Density Estimation. COLT Miroslav Dudík, Steven J. Phillips, Robert E. Schapire
2004	J	`jnl`	The Dynamics of AdaBoost: Cyclic Behavior and Convergence of Margins. J. Mach. Learn. Res. Cynthia Rudin, Ingrid Daubechies, Robert E. Schapire
2003	—	`conf`	Active learning for spoken language understanding. ICASSP (1) Gökhan Tür, Robert E. Schapire, Dilek Hakkani-Tür
2003	J	`jnl`	An Efficient Boosting Algorithm for Combining Preferences. J. Mach. Learn. Res. Yoav Freund, Raj D. Iyer, Robert E. Schapire, Yoram Singer
2003	J	`jnl`	Decision-Theoretic Bidding Based on Learned Density Models in Simultaneous, Interacting Auctions. J. Artif. Intell. Res. Peter Stone, Robert E. Schapire, Michael L. Littman, János A. Csirik, David A. McAllester
2003	—	`conf`	On the Dynamics of Boosting. NIPS Cynthia Rudin, Ingrid Daubechies, Robert E. Schapire
2002	A	`conf`	AT&t help desk. INTERSPEECH Giuseppe Di Fabbrizio, Dawn Dutton, Narendra K. Gupta, Barbara Hollister, Mazin G. Rahim, Giuseppe Riccardi, Robert E. Schapire, Juergen Schroeter
2002	—	`conf`	ATTac-2001: A Learning, Autonomous Bidding Agent. AMEC Peter Stone, Robert E. Schapire, János A. Csirik, Michael L. Littman, David A. McAllester
2002	A	`conf`	Advances in Boosting. UAI Robert E. Schapire
2002	Misc	`conf`	Combining prior knowledge and boosting for call classification in spoken language dialogue. ICASSP Marie Rochery, Robert E. Schapire, Mazin G. Rahim, Narendra K. Gupta, Giuseppe Riccardi, Srinivas Bangalore, Hiyan Alshawi, Shona Douglas
2002	A*	`conf`	Incorporating Prior Knowledge into Boosting. ICML Robert E. Schapire, Marie Rochery, Mazin G. Rahim, Narendra K. Gupta
2002	J	`jnl`	Logistic Regression, AdaBoost and Bregman Distances. Mach. Learn. Michael Collins, Robert E. Schapire, Yoram Singer
2002	A*	`conf`	Modeling Auction Price Uncertainty Using Boosting-based Conditional Density Estimation. ICML Robert E. Schapire, Peter Stone, David A. McAllester, Michael L. Littman, János A. Csirik
2002	J	`jnl`	The Nonstochastic Multiarmed Bandit Problem. SIAM J. Comput. Peter Auer, Nicolò Cesa-Bianchi, Yoav Freund, Robert E. Schapire
2001	—	`conf`	A Generalization of Principal Components Analysis to the Exponential Family. NIPS Michael Collins, Sanjoy Dasgupta, Robert E. Schapire
2001	J	`jnl`	Drifting Games. Mach. Learn. Robert E. Schapire
2001	A	`conf`	Why averaging classifiers can protect against overfitting. AISTATS Yoav Freund, Yishay Mansour, Robert E. Schapire
2000	J	`jnl`	BoosTexter: A Boosting-based System for Text Categorization. Mach. Learn. Robert E. Schapire, Yoram Singer
2000	A	`conf`	Boosting for Document Routing. CIKM Raj D. Iyer, David D. Lewis, Robert E. Schapire, Yoram Singer, Amit Singhal
2000	J	`jnl`	Gambling in a rigged casino: The adversarial multi-armed bandit problem Electron. Colloquium Comput. Complex. Peter Auer, Nicolò Cesa-Bianchi, Yoav Freund, Robert E. Schapire
2000	A*	`conf`	Logistic Regression, AdaBoost and Bregman Distances. COLT Michael Collins, Robert E. Schapire, Yoram Singer
2000	A*	`conf`	On the Convergence Rate of Good-Turing Estimators. COLT David A. McAllester, Robert E. Schapire
2000	A*	`conf`	Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers. ICML Erin L. Allwein, Robert E. Schapire, Yoram Singer
2000	J	`jnl`	Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers. J. Mach. Learn. Res. Erin L. Allwein, Robert E. Schapire, Yoram Singer
1999	A*	`conf`	A Brief Introduction to Boosting. IJCAI Robert E. Schapire
1999	A*	`conf`	Boosting Applied to Tagging and PP Attachment. EMNLP Steven Abney, Robert E. Schapire, Yoram Singer
1999	A*	`conf`	Drifting Games. COLT Robert E. Schapire
1999	J	`jnl`	Improved Boosting Algorithms Using Confidence-rated Predictions. Mach. Learn. Robert E. Schapire, Yoram Singer
1999	J	`jnl`	Large Margin Classification Using the Perceptron Algorithm. Mach. Learn. Yoav Freund, Robert E. Schapire
1999	J	`jnl`	Learning to Order Things. J. Artif. Intell. Res. William W. Cohen, Robert E. Schapire, Yoram Singer
1999	B	`conf`	Theoretical Views of Boosting and Applications. ALT Robert E. Schapire
1999	—	`conf`	Theoretical Views of Boosting. EuroCOLT Robert E. Schapire
1998	A*	`conf`	An Efficient Boosting Algorithm for Combining Preferences. ICML Yoav Freund, Raj D. Iyer, Robert E. Schapire, Yoram Singer
1998	A*	`conf`	Boosting and Rocchio Applied to Text Filtering. SIGIR Robert E. Schapire, Yoram Singer, Amit Singhal
1998	A*	`conf`	Improved Boosting Algorithms using Confidence-Rated Predictions. COLT Robert E. Schapire, Yoram Singer
1998	A*	`conf`	Large Margin Classification Using the Perceptron Algorithm. COLT Yoav Freund, Robert E. Schapire
1997	J	`jnl`	A Comparison of New and Old Algorithms for a Mixture Estimation Problem. Mach. Learn. David P. Helmbold, Robert E. Schapire, Yoram Singer, Manfred K. Warmuth
1997	J	`jnl`	A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting. J. Comput. Syst. Sci. Yoav Freund, Robert E. Schapire
1997	A*	`conf`	Boosting the margin: A new explanation for the effectiveness of voting methods. ICML Robert E. Schapire, Yoav Freund, Peter Barlett, Wee Sun Lee
1997	J	`jnl`	Efficient Learning of Typical Finite Automata from Random Walks. Inf. Comput. Yoav Freund, Michael J. Kearns, Dana Ron, Ronitt Rubinfeld, Robert E. Schapire, Linda Sellie
1997	J	`jnl`	How to use expert advice. J. ACM Nicolò Cesa-Bianchi, Yoav Freund, David Haussler, David P. Helmbold, Robert E. Schapire, Manfred K. Warmuth
1997	—	`conf`	Learning to Order Things. NIPS William W. Cohen, Robert E. Schapire, Yoram Singer
1997	J	`jnl`	Predicting Nearly As Well As the Best Pruning of a Decision Tree. Mach. Learn. David P. Helmbold, Robert E. Schapire
1997	A*	`ed.`	Proceedings of the Tenth Annual Conference on Computational Learning Theory, COLT 1997, Nashville, Tennessee, USA, July 6-9, 1997. COLT Yoav Freund, Robert E. Schapire
1997	A*	`conf`	Using and Combining Predictors That Specialize. STOC Yoav Freund, Robert E. Schapire, Yoram Singer, Manfred K. Warmuth
1997	A*	`conf`	Using output codes to boost multiclass learning problems. ICML Robert E. Schapire
1996	A*	`conf`	Experiments with a New Boosting Algorithm. ICML Yoav Freund, Robert E. Schapire
1996	A*	`conf`	Game Theory, On-Line Prediction and Boosting. COLT Yoav Freund, Robert E. Schapire
1996	J	`jnl`	Learning Sparse Multivariate Polynomials over a Field with Queries and Counterexamples. J. Comput. Syst. Sci. Robert E. Schapire, Linda Sellie
1996	J	`jnl`	On the Worst-Case Analysis of Temporal-Difference Learning Algorithms. Mach. Learn. Robert E. Schapire, Manfred K. Warmuth
1996	A*	`conf`	On-Line Portfolio Selection Using Multiplicative Updates. ICML David P. Helmbold, Robert E. Schapire, Yoram Singer, Manfred K. Warmuth
1996	A*	`conf`	Training Algorithms for Linear Text Classifiers. SIGIR David D. Lewis, Robert E. Schapire, James P. Callan, Ron Papka
1995	A*	`conf`	A Comparison of New and Old Algorithms for a Mixture Estimation Problem. COLT David P. Helmbold, Yoram Singer, Robert E. Schapire, Manfred K. Warmuth
1995	—	`conf`	A decision-theoretic generalization of on-line learning and an application to boosting. EuroCOLT Yoav Freund, Robert E. Schapire
1995	A*	`conf`	Efficient Algorithms for Learning to Play Repeated Games Against Computationally Bounded Adversaries. FOCS Yoav Freund, Michael J. Kearns, Yishay Mansour, Dana Ron, Ronitt Rubinfeld, Robert E. Schapire
1995	A*	`conf`	Gambling in a Rigged Casino: The Adversarial Multi-Arm Bandit Problem. FOCS Peter Auer, Nicolò Cesa-Bianchi, Yoav Freund, Robert E. Schapire
1995	J	`jnl`	On the Sample Complexity of Weakly Learning Inf. Comput. Sally A. Goldman, Michael J. Kearns, Robert E. Schapire
1995	A*	`conf`	Predicting Nearly as Well as the Best Pruning of a Decision Tree. COLT David P. Helmbold, Robert E. Schapire
1994	J	`jnl`	Bounds on the Sample Complexity of Bayesian Learning Using Information Theory and the VC Dimension. Mach. Learn. David Haussler, Michael J. Kearns, Robert E. Schapire
1994	J	`jnl`	Diversity-Based Inference of Finite Automata. J. ACM Ronald L. Rivest, Robert E. Schapire
1994	J	`jnl`	Efficient Distribution-Free Learning of Probabilistic Concepts. J. Comput. Syst. Sci. Michael J. Kearns, Robert E. Schapire
1994	J	`jnl`	Learning Probabilistic Read-once Formulas on Product Distributions. Mach. Learn. Robert E. Schapire
1994	A*	`conf`	On the Worst-Case Analysis of Temporal-Difference Learning Algorithms. ICML Robert E. Schapire, Manfred K. Warmuth
1994	A*	`conf`	On the learnability of discrete distributions. STOC Michael J. Kearns, Yishay Mansour, Dana Ron, Ronitt Rubinfeld, Robert E. Schapire, Linda Sellie
1994	J	`jnl`	Toward Efficient Agnostic Learning. Mach. Learn. Michael J. Kearns, Robert E. Schapire, Linda Sellie
1993	J	`jnl`	Boosting Performance in Neural Networks. Int. J. Pattern Recognit. Artif. Intell. Harris Drucker, Robert E. Schapire, Patrice Y. Simard
1993	A*	`conf`	Efficient learning of typical finite automata from random walks. STOC Yoav Freund, Michael J. Kearns, Dana Ron, Ronitt Rubinfeld, Robert E. Schapire, Linda Sellie
1993	J	`jnl`	Exact Identification of Read-Once Formulas Using Fixed Points of Amplification Functions. SIAM J. Comput. Sally A. Goldman, Michael J. Kearns, Robert E. Schapire
1993	A*	`conf`	How to use expert advice. STOC Nicolò Cesa-Bianchi, Yoav Freund, David P. Helmbold, David Haussler, Robert E. Schapire, Manfred K. Warmuth
1993	J	`jnl`	Inference of Finite Automata Using Homing Sequences Inf. Comput. Ronald L. Rivest, Robert E. Schapire
1993	—	`conf`	Inference of Finite Automata Using Homing Sequences. Machine Learning: From Theory to Applications Ronald L. Rivest, Robert E. Schapire
1993	J	`jnl`	Learning Binary Relations and Total Orders. SIAM J. Comput. Sally A. Goldman, Ronald L. Rivest, Robert E. Schapire
1993	A*	`conf`	Learning Sparse Multivariate Polynomials over a Field with Queries and Counterexamples. COLT Robert E. Schapire, Linda Sellie
1992	—	`book`	Design and analysis of efficient learning algorithms. Robert E. Schapire
1992	—	`conf`	Improving Performance in Neural Networks Using a Boosting Algorithm. NIPS Harris Drucker, Robert E. Schapire, Patrice Y. Simard
1992	A*	`conf`	Toward Efficient Agnostic Learning. COLT Michael J. Kearns, Robert E. Schapire, Linda Sellie
1991	A*	`conf`	Bounds on the Sample Complexity of Bayesian Learning Using Information Theory and the VC Dimension. COLT David Haussler, Michael J. Kearns, Robert E. Schapire
1991	—	`conf`	Estimating Average-Case Learning Curves Using Bayesian, Statistical Physics and VC Dimension Methods. NIPS David Haussler, Michael J. Kearns, Manfred Opper, Robert E. Schapire
1991	A*	`conf`	Learning Probabilistic Read-Once Formulas on Product Distributions. COLT Robert E. Schapire
1990	A*	`conf`	Efficient Distribution-Free Learning of Probabilistic Concepts (Abstract). COLT Michael J. Kearns, Robert E. Schapire
1990	A*	`conf`	Efficient Distribution-free Learning of Probabilistic Concepts (Extended Abstract) FOCS Michael J. Kearns, Robert E. Schapire
1990	A*	`conf`	Exact Identification of Circuits Using Fixed Points of Amplification Functions (Abstract). COLT Sally A. Goldman, Michael J. Kearns, Robert E. Schapire
1990	A*	`conf`	Exact Identification of Circuits Using Fixed Points of Amplification Functions (Extended Abstract) FOCS Sally A. Goldman, Michael J. Kearns, Robert E. Schapire
1990	A*	`conf`	On the Sample Complexity of Weak Learning. COLT Sally A. Goldman, Michael J. Kearns, Robert E. Schapire
1990	A*	`conf`	Pattern Languages are not Learnable. COLT Robert E. Schapire
1990	J	`jnl`	The Strength of Weak Learnability. Mach. Learn. Robert E. Schapire
1989	A*	`conf`	Inference of Finite Automata Using Homing Sequences (Extended Abstract) STOC Ronald L. Rivest, Robert E. Schapire
1989	A*	`conf`	Learning Binary Relations and Total Orders (Extended Abstract) FOCS Sally A. Goldman, Ronald L. Rivest, Robert E. Schapire
1989	A*	`conf`	The Strength of Weak Learnability (Extended Abstract) FOCS Robert E. Schapire
1987	A*	`conf`	Diversity-Based Inference of Finite Automata (Extended Abstract) FOCS Ronald L. Rivest, Robert E. Schapire