Robert Schapire
#8,186
Most Influential Person Now
American computer scientist
Robert Schapire's AcademicInfluence.com Rankings
Robert Schapirecomputer-science Degrees
Computer Science
#380
World Rank
#395
Historical Rank
#216
USA Rank
Machine Learning
#26
World Rank
#26
Historical Rank
#10
USA Rank
Artificial Intelligence
#182
World Rank
#186
Historical Rank
#81
USA Rank
Database
#251
World Rank
#260
Historical Rank
#119
USA Rank
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Computer Science
Robert Schapire's Degrees
- Bachelors Mathematics Princeton University
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Why Is Robert Schapire Influential?
(Suggest an Edit or Addition)According to Wikipedia, Robert Elias Schapire is an American computer scientist, former David M. Siegel '83 Professor in the computer science department at Princeton University, and has recently moved to Microsoft Research. His primary specialty is theoretical and applied machine learning.
Robert Schapire's Published Works
Number of citations in a given year to any of this author's works
Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author
Published Works
- A decision-theoretic generalization of on-line learning and an application to boosting (1997) (19082)
- Maximum entropy modeling of species geographic distributions (2006) (13050)
- Experiments with a New Boosting Algorithm (1996) (9118)
- Novel methods improve prediction of species' distributions from occurrence data (2006) (7535)
- The Strength of Weak Learnability (1990) (4156)
- Improved Boosting Algorithms Using Confidence-rated Predictions (1998) (3501)
- A Short Introduction to Boosting (1999) (3321)
- Boosting the margin: A new explanation for the effectiveness of voting methods (1997) (2946)
- A contextual-bandit approach to personalized news article recommendation (2010) (2366)
- BoosTexter: A Boosting-based System for Text Categorization (2000) (2355)
- An Efficient Boosting Algorithm for Combining Preferences (1998) (2271)
- The Nonstochastic Multiarmed Bandit Problem (2002) (2154)
- Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers (2000) (2080)
- A maximum entropy approach to species distribution modeling (2004) (2027)
- The Boosting Approach to Machine Learning An Overview (2003) (2026)
- Large Margin Classification Using the Perceptron Algorithm (1998) (1463)
- A Brief Introduction to Boosting (1999) (1388)
- Opening the black box: an open-source release of Maxent (2017) (1231)
- Learning to Order Things (1997) (1002)
- Discussion of the Paper \additive Logistic Regression: a Statistical View of Boosting" By (2000) (950)
- Gambling in a rigged casino: The adversarial multi-armed bandit problem (1995) (871)
- Contextual Bandits with Linear Payoff Functions (2011) (812)
- Logistic Regression, AdaBoost and Bregman Distances (2000) (702)
- How to use expert advice (1993) (660)
- Training algorithms for linear text classifiers (1996) (636)
- Adaptive game playing using multiplicative weights (1999) (593)
- Explaining AdaBoost (2013) (568)
- Inference of finite automata using homing sequences (1989) (547)
- Hierarchical multi-label prediction of gene function (2006) (542)
- A Generalization of Principal Components Analysis to the Exponential Family (2001) (493)
- Toward efficient agnostic learning (1992) (453)
- Efficient distribution-free learning of probabilistic concepts (1990) (437)
- Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits (2014) (422)
- Game theory, on-line prediction and boosting (1996) (418)
- Boosting and Rocchio applied to text filtering (1998) (388)
- On‐Line Portfolio Selection Using Multiplicative Updates (1998) (364)
- Boosting: Foundations and Algorithms (2012) (325)
- Using output codes to boost multiclass learning problems (1997) (325)
- Contextual Decision Processes with low Bellman rank are PAC-Learnable (2016) (309)
- On the learnability of discrete distributions (1994) (292)
- A Game-Theoretic Approach to Apprenticeship Learning (2007) (286)
- Using and combining predictors that specialize (1997) (275)
- Contextual Bandit Algorithms with Supervised Learning Guarantees (2010) (271)
- Combining active and semi-supervised learning for spoken language understanding (2005) (238)
- Performance Guarantees for Regularized Maximum Entropy Density Estimation (2004) (236)
- How boosting the margin can also boost classifier complexity (2006) (231)
- Boosting Performance in Neural Networks (1993) (229)
- Apprenticeship learning using linear programming (2008) (228)
- Correcting sample selection bias in maximum entropy density estimation (2005) (225)
- Maximum Entropy Density Estimation with Generalized Regularization and an Application to Species Distribution Modeling (2007) (225)
- How to use expert advice (1997) (215)
- Algorithms for portfolio management based on the Newton method (2006) (210)
- Improving Performance in Neural Networks Using a Boosting Algorithm (1992) (204)
- The non-stochastic multi-armed bandit problem (2001) (201)
- Theoretical Views of Boosting and Applications (1999) (187)
- Adding dense, weighted connections to WordNet (2005) (171)
- Fast Convergence of Regularized Learning in Games (2015) (170)
- Bounds on the sample complexity of Bayesian learning using information theory and the VC dimension (1992) (161)
- Predicting Nearly As Well As the Best Pruning of a Decision Tree (1995) (159)
- Boosting Applied to Tagging and PP Attachment (1999) (154)
- Incorporating Prior Knowledge into Boosting (2002) (148)
- Diversity-based inference of finite automata (1994) (137)
- On the Convergence Rate of Good-Turing Estimators (2000) (137)
- Theoretical Views of Boosting (1999) (135)
- A theory of multiclass boosting (2010) (131)
- Toward Efficient Agnostic Learning (1992) (131)
- Corralling a Band of Bandit Algorithms (2016) (121)
- The Dynamics of AdaBoost: Cyclic Behavior and Convergence of Margins (2004) (117)
- Achieving All with No Parameters: AdaNormalHedge (2015) (116)
- Design and analysis of efficient learning algorithms (1992) (113)
- Margin-based Ranking and an Equivalence between AdaBoost and RankBoost (2009) (109)
- FilterBoost: Regression and Classification on Large Datasets (2007) (99)
- Learning binary relations and total orders (1989) (98)
- Faster solutions of the inverse pairwise Ising problem (2007) (96)
- Efficient learning of typical finite automata from random walks (1993) (95)
- Active learning for spoken language understanding (2003) (88)
- Learning Deep ResNet Blocks Sequentially using Boosting Theory (2017) (85)
- Generalization bounds for averaged classifiers (2004) (84)
- Margin-Based Ranking Meets Boosting in the Middle (2005) (83)
- Learning sparse multivariate polynomials over a field with queries and counterexamples (1993) (81)
- A Comparison of New and Old Algorithms for a Mixture Estimation Problem (1995) (81)
- Practical Contextual Bandits with Regression Oracles (2018) (77)
- On Oracle-Efficient PAC RL with Rich Observations (2018) (74)
- Non-Stochastic Bandit Slate Problems (2010) (73)
- Decision-Theoretic Bidding Based on Learned Density Models in Simultaneous, Interacting Auctions (2003) (71)
- Boosting for document routing (2000) (70)
- Contextual Dueling Bandits (2015) (69)
- A Reduction from Apprenticeship Learning to Classification (2010) (68)
- Modeling Auction Price Uncertainty Using Boosting-based Conditional Density Estimation (2002) (65)
- Adversarial Bandits with Knapsacks (2018) (64)
- Reinforcement Learning with Convex Constraints (2019) (63)
- Efficient Algorithms for Adversarial Contextual Learning (2016) (62)
- Contextual Bandit Learning with Predictable Rewards (2012) (60)
- The Rate of Convergence of Adaboost (2011) (60)
- A new approach to unsupervised learning in deterministic environments (1990) (59)
- The strength of weak learnability (1989) (58)
- Maximum Entropy Distribution Estimation with Generalized Regularization (2006) (58)
- Boosting with prior knowledge for call classification (2005) (57)
- Learning and inference in the presence of corrupted inputs (2015) (56)
- Toward Eecient Agnostic Learning (1992) (52)
- Drifting Games (1999) (52)
- Why averaging classifiers can protect against overfitting (2001) (48)
- Convergence and Consistency of Regularized Boosting Algorithms with Stationary B-Mixing Observations (2005) (48)
- Efficient algorithms for learning to play repeated games against computationally bounded adversaries (1995) (43)
- Exploratory Gradient Boosting for Reinforcement Learning in Complex Domains (2016) (43)
- Efficient and Parsimonious Agnostic Active Learning (2015) (42)
- Exact identification of circuits using fixed points of amplification functions (1990) (41)
- Exact Identification of Read-Once Formulas Using Fixed Points of Amplification Functions (1993) (41)
- Pattern languages are not learnable (1990) (41)
- Oracle-Efficient Online Learning and Auction Design (2016) (40)
- The Minimal Disagreement Parity Problem as a Hard Satisfiability Problem (1995) (40)
- Analysis of boosting algorithms using the smooth margin function (2007) (37)
- ATTac-2001: A Learning, Autonomous Bidding Agent (2002) (36)
- Improved Regret Bounds for Oracle-Based Adversarial Contextual Bandits (2016) (36)
- Gradient descent follows the regularization path for general losses (2020) (35)
- On the Worst-Case Analysis of Temporal-Difference Learning Algorithms (2005) (35)
- Discussion of the paper "Arcing Classifiers" by Leo Breiman (1998) (34)
- Bounds on the Sample Complexity of Bayesian Learning Using Information Theory and the VC Dimension (1991) (34)
- Error Adaptive Classifier Boosting (EACB): Leveraging Data-Driven Training Towards Hardware Resilience for Signal Inference (2015) (32)
- A Drifting-Games Analysis for Online Learning and Applications to Boosting (2014) (29)
- Diversity-Based Inference of Finite Automata (Extended Abstract) (1987) (29)
- Combining prior knowledge and boosting for call classification in spoken language dialogue (2002) (28)
- Speed and Sparsity of Regularized Boosting (2009) (28)
- An Optimal High Probability Algorithm for the Contextual Bandit Problem (2010) (26)
- Maximum Entropy Correlated Equilibria (2007) (26)
- On reoptimizing multi-class classifiers (2008) (26)
- Boosting Based on a Smooth Margin (2004) (26)
- Hierarchical maximum entropy density estimation (2007) (25)
- The Convergence Rate of AdaBoost (2010) (24)
- Machine Learning Algorithms for Classification (2007) (23)
- Towards Minimax Online Learning with Unknown Time Horizon (2013) (22)
- Open Problem: First-Order Regret Bounds for Contextual Bandits (2017) (21)
- Bayesian decision-making under misspecified priors with applications to meta-learning (2021) (21)
- Interactive Learning from Activity Description (2021) (20)
- AT&t help desk (2002) (19)
- BoosTexter: A System for Multiclass Multi-label Text Categorization (1998) (19)
- Error-adaptive classifier boosting (EACB): Exploiting data-driven training for highly fault-tolerant hardware (2014) (17)
- Achieving All with No Parameters: Adaptive NormalHedge (2015) (16)
- Functional Frank-Wolfe Boosting for General Loss Functions (2015) (16)
- Learning probabilistic read-once formulas on product distributions (1991) (16)
- On the Dynamics of Boosting (2003) (16)
- On the worst-case analysis of temporal-difference learning algorithms (2004) (16)
- Boosting (2012) (15)
- Estimating Average-Case Learning Curves Using Bayesian, Statistical Physics and VC Dimension Methods (1991) (14)
- Learning with continuous experts using drifting games (2008) (14)
- On the sample complexity of weak learning (1990) (14)
- Deterministic compressed sensing (2011) (13)
- Efficient Distribution-free Learning of Probabilistic Concepts (Extended Abstract) (1990) (13)
- Contextual search in the presence of irrational agents (2020) (13)
- Imitation Learning with a Value-Based Prior (2007) (13)
- Inference of Finite Automata Using Homing Sequences (Extended Abstract) (1989) (13)
- Robust Inference for Multiclass Classification (2018) (12)
- The Strength of Weak Learnability (Extended Abstract) (1989) (12)
- A game theoretic approach to expander-based compressive sensing (2011) (12)
- Instance-dependent Regret Bounds for Dueling Bandits (2016) (11)
- Precise Statements of Convergence for AdaBoost and arc-gv (2007) (11)
- Efficient Distribution-Free Learning of Probabilistic (1994) (11)
- Learning theory and language modeling (2003) (10)
- On Oracle-Efficient PAC Reinforcement Learning with Rich Observations (2018) (10)
- The Emerging Theory of Average-Case Complexity (1990) (10)
- Reinforcement learning without rewards (2010) (9)
- On Polynomial Time PAC Reinforcement Learning with Rich Observations (2018) (9)
- Oracle-Efficient Learning and Auction Design (2016) (9)
- Convergence and Consistency of Regularized Boosting With Weakly Dependent Observations (2014) (8)
- From Optimization to Regret Minimization and Back Again (2008) (7)
- A Discussion of: "Process Consistency for AdaBoost" by Wenxin Jiang "On the Bayes-risk consistency of regularized boosting methods" by G´ abor Lugosi and Nicolas Vayatis "Statistical Behavior and Consistency of Classification Methods based on Convex Risk Minimization" by Tong Zhang (2004) (7)
- Compressive sensing meets game theory (2011) (7)
- Advances in Boosting (2002) (7)
- Discussions of boosting papers, and rejoinders (2004) (7)
- Unsupervised Domain Adaptation Using Approximate Label Matching (2016) (6)
- Efficient Multiclass Implementations of L1-Regularized Maximum Entropy (2005) (6)
- Collaborative Place Models (2015) (6)
- A Bayesian Boosting Model (2012) (5)
- Aneuploidy prediction and tumor classification with heterogeneous hidden conditional random fields (2008) (4)
- Response to Mease and Wyner, Evidence Contrary to the Statistical View of Boosting, JMLR 9:131-156, 2008 (2008) (4)
- On the Sample Complexity of Weakly Learning (1995) (4)
- Efficient distribution-free learning of probabilistic concepts (abstract) (1990) (4)
- Learning Probabilistic Read-once Formulas on Product Distributions (1991) (4)
- Interactive Learning of a Dynamic Structure (2020) (3)
- Multiclass Boosting and the Cost of Weak Learning (2021) (3)
- Boosting, margins, and dynamics (2004) (3)
- Foundations of Machine Learning (2012) (3)
- Learning Binary Relations and Total Orders (Extended Abstract) (1989) (3)
- Collaborative Ranking for Local Preferences (2014) (3)
- Multi-Source Domain Adaptation Using Approximate Label Matching (2016) (2)
- Robust Multi-objective Learning with Mentor Feedback (2014) (2)
- Convex Analysis at Infinity: An Introduction to Astral Space (2022) (2)
- Open Problem: Does AdaBoost Always Cycle? (2012) (2)
- COS 511 : Foundations of Machine Learning (2006) (2)
- Using AdaBoost to Minimize Training Error (2012) (2)
- BOOSTEXTER FOR TEXT CATEGORIZATION IN SPOKEN LANGUAGE DIALOGUE (2007) (2)
- A Game-Theoretic Approach to Apprenticeship Learning — Supplement (2008) (2)
- Cos 511: Theoretical Machine Learning 1 Review of Last Lecture 2 Randomized Weighted Majority Algorithm (rwma) (2008) (1)
- Analyzing Margins in Boosting (2005) (1)
- Game theory and optimization in boosting (2011) (1)
- Online Learning with Unknown Time Horizon (2013) (1)
- Provably Sample-Efficient RL with Side Information about Latent Dynamics (2022) (1)
- Game Theory, Online Learning, and Boosting (2012) (1)
- Using Confidence-Rated Weak Predictions (2012) (1)
- Combining Spatial and Telemetric Features for Learning Animal Movement Models (2010) (1)
- Multiclass Classification Problems (2012) (1)
- Adding Dense, Weighted Connections to W ORD N ET (2005) (1)
- Supplement : A Theory of Multiclass Boosting (2010) (1)
- Using structural information in machine learning applications (2008) (1)
- Loss Minimization and Generalizations of Boosting (2012) (1)
- Agent Mediated Electronic Commerce IV : Designing Mechanisms and Systems , Springer Verlag , 2002 . ATTac-2001 : A Learning , Autonomous Bidding Agent (2015) (0)
- Exploration Strategies for Model-based Learning 37 Convergence Results for Single-step On-policy Reinforcement-learning Algorithms. Machine Learning Journal Exploration Strategies for Model-based Learning Exploration Strategies for Model-based Learning (2007) (0)
- Cos 511: Theoretical Machine Learning 2 Relative Entropy and Chernoff Bounds 2.1 Relative Entropy (2008) (0)
- Advances in Boosting (Invited Talk) (2013) (0)
- Error Correcting Output Codes (2010) (0)
- A ShortIntroductionto Boosting Yoav Freund RobertE . Schapire AT & T Labs (2000) (0)
- Contextual Search in the Presence of Adversarial Corruptions (2020) (0)
- The Contextual Bandits Problem: Techniques for Learning to Make High-Reward Decisions (2017) (0)
- Place Recommendation with Implicit Spatial Feedback (0)
- Subject and Author Index (2017) (0)
- The Margins Explanation for Boosting's Effectiveness (2012) (0)
- Submitted to the Annals of Statistics ANALYSIS OF BOOSTING ALGORITHMS USING THE SMOOTH MARGIN FUNCTION ∗ By (2007) (0)
- Appendix: Some Notation, Definitions, and Mathematical Background (2012) (0)
- SIGIR ’ 98 Boosting and Rocchio Applied to Text Filtering (2015) (0)
- Final Program Report : SAMSI Computational Advertising Program Summer (2012) (0)
- Data and text mining Aneuploidy prediction and tumor classification with heterogeneous hidden conditional random fields (2009) (0)
- Feature Induction Using Boosting and Logistic Regression on fMRI Images (2006) (0)
- LG ] 8 F eb 2 01 6 Efficient Algorithms for Adversarial Contextual Learning (2018) (0)
- Uncertainty in Artificial Intelligence : Proceedings of the Eighteenth Conference , 2002 . Advances in Boosting (2015) (0)
- Attaining the Best Possible Accuracy (2012) (0)
- Proceedings of the Tenth Annual Conference on Computational Learning Theory, COLT 1997, Nashville, Tennessee, USA, July 6-9, 1997 (1997) (0)
- Collaborative Ranking for Local Preferences Supplement (2014) (0)
- COMPRESSED SENSING MEETS GAME THEORY (2010) (0)
- Optimally Efficient Boosting (2012) (0)
- Boosting, Convex Optimization, and Information Geometry (2012) (0)
- Index of Algorithms, Figures, and Tables (2012) (0)
- Direct Bounds on the Generalization Error (2012) (0)
- Adding Dense , Weighted Connections to W ORD (2018) (0)
- Learning to Rank (2018) (0)
- Ju n 20 05 Efficient Multiclass Implementations of L 1-Regularized Maximum Entropy (2005) (0)
- Boosting in Continuous Time (2012) (0)
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