About
Discord Stateoftheart AI
GitHub

Publications

264

Cited by

107195

Robert Schapire

machine learning

Microsoft Research

Papers and Citations

1 - 50
A decision-theoretic generalization of on-line learning and an application to boosting
1997
Yoav Freund
Robert Schapire
Cited by 20279
Maximum entropy modeling of species geographic distributions
2006
Steven J Phillips
Robert Schapire
Robert P. Anderson
Cited by 12596
Experiments with a new boosting algorithm
1996
Yoav Freund
Robert Schapire
Cited by 9930
Novel methods improve prediction of species’ distributions from occurrence data
2006
Miroslav Dudik
Robert Schapire
Jin Li
+24
Cited by 7239
The strength of weak learnability
1990
Robert Schapire
Cited by 5455
Improved boosting algorithms using confidence-rated predictions
1999
Yoram Singer
Robert Schapire
Cited by 4313
A short introduction to boosting
1999
Yoav Freund
Robert Schapire
Naokie Abe
Cited by 3832
Boosting the margin: A new explanation for the effectiveness of voting methods
1998
Wee Sun Lee
Yoav Freund
Peter Bartlett
+1
Cited by 3331
Foundations of machine learning
2012
Yoav Freund
Robert Schapire
Cited by 3045
BoosTexter: A boosting-based system for text categorization
2000
Robert Schapire
Yoram Singer
Cited by 2797
An efficient boosting algorithm for combining preferences
2003
Yoav Freund
Yoram Singer
Robert Schapire
+1
Cited by 2604
Reducing multiclass to binary: A unifying approach for margin classifiers
2000
Robert Schapire
Yoram Singer
EL Allwein
Cited by 2407
The boosting approach to machine learning: An overview
2003
Robert Schapire
Cited by 2341
A Maximum Entropy Approach to Species Distribution Modeling
2004
Robert Schapire
Steven J Phillips
M Dudík
Cited by 2333
The nonstochastic multiarmed bandit problem
2002
Nicolò Cesa-Bianchi
Peter Auer
Robert Schapire
+1
Cited by 1913
A contextual-bandit approach to personalized news article recommendation
2010
John Langford
Robert Schapire
L Li
+1
Cited by 1702
Large margin classification using the perceptron algorithm
1999
Yoav Freund
Robert Schapire
Cited by 1643
A brief introduction to boosting
1999
Robert Schapire
Cited by 1507
Learning to order things
1998
Yoram Singer
William W. Cohen
Robert Schapire
Cited by 1050
How to use expert advice
1997
Yoav Freund
Nicolò Cesa-Bianchi
Robert Schapire
+3
Cited by 891
Logistic regression, AdaBoost and Bregman distances
2002
Michael Collins
Yoram Singer
Robert Schapire
Cited by 835
Training algorithms for linear text classifiers
1996
David D. Lewis
Robert Schapire
R Papka
+1
Cited by 815
Gambling in a rigged casino: The adversarial multi-armed bandit problem
1995
Nicolò Cesa-Bianchi
Peter Auer
Yoav Freund
+1
Cited by 807
Contextual bandits with linear payoff functions
2011
Lihong Li
Wei Chu（褚崴）
Lev Reyzin
+3
Cited by 634
Inference of finite automata using homing sequences
1993
Robert Schapire
Ronald L. Rivest
Cited by 588
Hierarchical multi-label prediction of gene function
2006
Robert Schapire
Olga Troyanskaya
Zafer Barutcuoglu
Cited by 587
Opening the black box: An open‐source release of Maxent
2017
SJ Phillips
M Dudík
ME Blair
+2
Cited by 567
Toward efficient agnostic learning
1994
Michael Kearns
Robert Schapire
LM Sellie
Cited by 559
Adaptive game playing using multiplicative weights
1999
Robert Schapire
Yoav Freund
Cited by 533
A generalization of principal components analysis to the exponential family
2002
Robert Schapire
Michael Collins
Sanjoy Dasgupta
Cited by 519
Game theory, on-line prediction and boosting
1996
Robert Schapire
Yoav Freund
Cited by 458
Boosting and Rocchio applied to text filtering
1998
Yoram Singer
Robert Schapire
A Singhal
Cited by 445
Explaining adaboost
2013
Robert Schapire
Cited by 414
Using output codes to boost multiclass learning problems
1997
Robert Schapire
Cited by 387
On‐line portfolio selection using multiplicative updates
1998
Robert Schapire
Yoram Singer
Manfred K. Warmuth
+1
Cited by 360
Taming the monster: A fast and simple algorithm for contextual bandits
2014
Lihong Li
Satyen Kale
Daniel Hsu
+4
Cited by 323
Bounds on the sample complexity of Bayesian learning using information theory and the VC dimension
1994
Michael Kearns
Robert Schapire
David Haussler
Cited by 304
Using and combining predictors that specialize
1997
Yoram Singer
Robert Schapire
Yoav Freund
+1
Cited by 290
On the learnability of discrete distributions
1994
Michael Kearns
Dana Ron
Ronitt Rubinfeld
+3
Cited by 287
Efficient distribution-free learning of probabilistic concepts
1994
Michael Kearns
Robert Schapire
Cited by 285
Boosting performance in neural networks
1993
Robert Schapire
Patrice Simard
H Drucker
Cited by 282
Combining active and semi-supervised learning for spoken language understanding
2005
Gokhan Tur
Robert Schapire
D Hakkani-Tür
Cited by 280
Performance guarantees for regularized maximum entropy density estimation
2004
Miroslav Dudik
Steven J Phillips
Robert Schapire
Cited by 270
Improving performance in neural networks using a boosting algorithm
1993
Patrice Simard
Robert Schapire
H Drucker
Cited by 252
A game-theoretic approach to apprenticeship learning
2008
Robert Schapire
Umar Syed
Cited by 251
How boosting the margin can also boost classifier complexity
2006
Lev Reyzin
Robert Schapire
Cited by 246
Maximum entropy density estimation with generalized regularization and an application to species distribution modeling
2007
Robert Schapire
Steven J Phillips
M Dudík
Cited by 233
Theoretical views of boosting and applications
1999
Robert Schapire
Cited by 231
Correcting sample selection bias in maximum entropy density estimation
2006
Steven J Phillips
Robert Schapire
M Dudík
Cited by 209
Margin-based ranking and an equivalence between AdaBoost and RankBoost
2009
Cynthia Rudin
Robert Schapire
Cited by 199