Communications of the ACM
Learnability and the Vapnik-Chervonenkis dimension
Journal of the ACM (JACM)
COLT '90 Proceedings of the third annual workshop on Computational learning theory
Learning probabilistic prediction functions
COLT '88 Proceedings of the first annual workshop on Computational learning theory
From on-line to batch learning
COLT '89 Proceedings of the second annual workshop on Computational learning theory
Journal of Algorithms
Competitive algorithms for layered graph traversal
SFCS '91 Proceedings of the 32nd annual symposium on Foundations of computer science
Equivalence of models for polynomial learnability
Information and Computation
Universal forecasting algorithms
Information and Computation
STOC '93 Proceedings of the twenty-fifth annual ACM symposium on Theory of computing
Approximate methods for sequential decision making using expert advice
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
Competitive k-server algorithms
Journal of Computer and System Sciences - Special issue: 31st IEEE conference on foundations of computer science, Oct. 22–24, 1990
Efficient distribution-free learning of probabilistic concepts
Journal of Computer and System Sciences - Special issue: 31st IEEE conference on foundations of computer science, Oct. 22–24, 1990
The weighted majority algorithm
Information and Computation
Bounds on the Sample Complexity of Bayesian Learning Using Information Theory and the VC Dimension
Machine Learning - Special issue on computational learning theory
Predicting {0, 1}-functions on randomly drawn points
Information and Computation
Toward Efficient Agnostic Learning
Machine Learning - Special issue on computational learning theory, COLT'92
A loss bound model for on-line stochastic prediction algorithms
Information and Computation
Journal of Computer and System Sciences
Using experts for predicting continuous outcomes
Euro-COLT '93 Proceedings of the first European conference on Computational learning theory
On-line learning of linear functions
Computational Complexity
On-line prediction and conversion strategies
Machine Learning
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Tight worst-case loss bounds for predicting with expert advice
EuroCOLT '95 Proceedings of the Second European Conference on Computational Learning Theory
Estimation of Dependences Based on Empirical Data: Springer Series in Statistics (Springer Series in Statistics)
Context-sensitive learning methods for text categorization
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
On sequential prediction of individual sequences relative to a set of experts
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
Large margin classification using the perceptron algorithm
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
Machine Learning - Special issue on context sensitivity and concept drift
Machine Learning - Special issue on context sensitivity and concept drift
The robustness of the p-norm algorithms
COLT '99 Proceedings of the twelfth annual conference on Computational learning theory
On prediction of individual sequences relative to a set of experts in the presence of noise
COLT '99 Proceedings of the twelfth annual conference on Computational learning theory
COLT '99 Proceedings of the twelfth annual conference on Computational learning theory
Linear relations between square-loss and Kolmogorov complexity
COLT '99 Proceedings of the twelfth annual conference on Computational learning theory
Large Margin Classification Using the Perceptron Algorithm
Machine Learning - The Eleventh Annual Conference on computational Learning Theory
Predicting nearly as well as the best pruning of a decision tree through dynamic programming scheme
Theoretical Computer Science
General linear relations between different types of predictive complexity
Theoretical Computer Science
Suboptimal measures of predictive complexity for absolute loss function
Information and Computation
Machine Learning
General Convergence Results for Linear Discriminant Updates
Machine Learning
On complexity of easy predictable sequences
Information and Computation
PAC-Bayesian Stochastic Model Selection
Machine Learning
Predicting nearly as well as the best pruning of a planar decision graph
Theoretical Computer Science
Potential-Based Algorithms in On-Line Prediction and Game Theory
Machine Learning
Combining Ordinal Financial Predictions with Genetic Programming
IDEAL '00 Proceedings of the Second International Conference on Intelligent Data Engineering and Automated Learning, Data Mining, Financial Engineering, and Intelligent Agents
EuroCOLT '99 Proceedings of the 4th European Conference on Computational Learning Theory
Structured Weight-Based Prediction Algorithms
ALT '98 Proceedings of the 9th International Conference on Algorithmic Learning Theory
Predicting Nearly as well as the best Pruning of a Planar Decision Graph
ALT '99 Proceedings of the 10th International Conference on Algorithmic Learning Theory
Genral Linear Relations among Different Types of Predictive Complexity
ALT '99 Proceedings of the 10th International Conference on Algorithmic Learning Theory
Non-linear Inequalities between Predictive and Kolmogorov Complexities
ALT '01 Proceedings of the 12th International Conference on Algorithmic Learning Theory
On-Line Algorithm to Predict Nearly as Well as the Best Pruning of a Decision Tree
Progress in Discovery Science, Final Report of the Japanese Discovery Science Project
Efficiently Approximating Weighted Sums with Exponentially Many Terms
COLT '01/EuroCOLT '01 Proceedings of the 14th Annual Conference on Computational Learning Theory and and 5th European Conference on Computational Learning Theory
Tracking a Small Set of Experts by Mixing Past Posteriors
COLT '01/EuroCOLT '01 Proceedings of the 14th Annual Conference on Computational Learning Theory and and 5th European Conference on Computational Learning Theory
Potential-Based Algorithms in Online Prediction and Game Theory
COLT '01/EuroCOLT '01 Proceedings of the 14th Annual Conference on Computational Learning Theory and and 5th European Conference on Computational Learning Theory
Discrete Prediction Games with Arbitrary Feedback and Loss
COLT '01/EuroCOLT '01 Proceedings of the 14th Annual Conference on Computational Learning Theory and and 5th European Conference on Computational Learning Theory
COLT '02 Proceedings of the 15th Annual Conference on Computational Learning Theory
A Second-Order Perceptron Algorithm
COLT '02 Proceedings of the 15th Annual Conference on Computational Learning Theory
Predictive Complexity and Information
COLT '02 Proceedings of the 15th Annual Conference on Computational Learning Theory
Mixability and the Existence of Weak Complexities
COLT '02 Proceedings of the 15th Annual Conference on Computational Learning Theory
Tracking a small set of experts by mixing past posteriors
The Journal of Machine Learning Research
The Robustness of the p-Norm Algorithms
Machine Learning
Optimality of universal Bayesian sequence prediction for general loss and alphabet
The Journal of Machine Learning Research
Tracking linear-threshold concepts with Winnow
The Journal of Machine Learning Research
Loss functions, complexities, and the legendre transformation
Theoretical Computer Science - Special issue: Algorithmic learning theory
How to Better Use Expert Advice
Machine Learning
Online Choice of Active Learning Algorithms
The Journal of Machine Learning Research
On approximating weighted sums with exponentially many terms
Journal of Computer and System Sciences
On-line prediction with kernels and the complexity approximation principle
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Online learning in online auctions
Theoretical Computer Science - Special issue: Online algorithms in memoriam, Steve Seiden
The best expert versus the smartest algorithm
Theoretical Computer Science - Special issue: Online algorithms in memoriam, Steve Seiden
Information markets vs. opinion pools: an empirical comparison
Proceedings of the 6th ACM conference on Electronic commerce
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
Predictive complexity and information
Journal of Computer and System Sciences - Special issue on COLT 2002
Journal of Computer and System Sciences - Special issue on COLT 2002
How many strings are easy to predict?
Information and Computation
Using additive expert ensembles to cope with concept drift
ICML '05 Proceedings of the 22nd international conference on Machine learning
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
Can machine learning be secure?
ASIACCS '06 Proceedings of the 2006 ACM Symposium on Information, computer and communications security
Online trading algorithms and robust option pricing
Proceedings of the thirty-eighth annual ACM symposium on Theory of computing
ICML '06 Proceedings of the 23rd international conference on Machine learning
Learning algorithms for online principal-agent problems (and selling goods online)
ICML '06 Proceedings of the 23rd international conference on Machine learning
Proceedings of the twenty-fifth annual ACM symposium on Principles of distributed computing
Combining expert advice in reactive environments
Journal of the ACM (JACM)
Online algorithms for market clearing
Journal of the ACM (JACM)
Improved second-order bounds for prediction with expert advice
Machine Learning
Regret Minimization Under Partial Monitoring
Mathematics of Operations Research
Graphical Models for Groups: Belief Aggregation and Risk Sharing
Decision Analysis
Real-time ranking with concept drift using expert advice
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Step decision rules for multistage stochastic programming: A heuristic approach
Automatica (Journal of IFAC)
Prediction with expert advice for the Brier game
Proceedings of the 25th international conference on Machine learning
Semi-supervised approach to rapid and reliable labeling of large data sets
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
An Unsupervised Learning Algorithm for Rank Aggregation
ECML '07 Proceedings of the 18th European conference on Machine Learning
Learning with Continuous Experts Using Drifting Games
ALT '08 Proceedings of the 19th international conference on Algorithmic Learning Theory
The weak aggregating algorithm and weak mixability
Journal of Computer and System Sciences
Unsupervised Classifier Selection Based on Two-Sample Test
DS '08 Proceedings of the 11th International Conference on Discovery Science
Approximation algorithms for restless bandit problems
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Multi-armed Bandits with Metric Switching Costs
ICALP '09 Proceedings of the 36th Internatilonal Collogquium on Automata, Languages and Programming: Part II
Online Markov Decision Processes
Mathematics of Operations Research
Can we learn to beat the best stock
Journal of Artificial Intelligence Research
An experts algorithm for transfer learning
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Regret Minimization and Job Scheduling
SOFSEM '10 Proceedings of the 36th Conference on Current Trends in Theory and Practice of Computer Science
How many strings are easy to predict?
Information and Computation
Learning Permutations with Exponential Weights
The Journal of Machine Learning Research
Prediction With Expert Advice For The Brier Game
The Journal of Machine Learning Research
The Journal of Machine Learning Research
A new understanding of prediction markets via no-regret learning
Proceedings of the 11th ACM conference on Electronic commerce
Learning with continuous experts using drifting games
Theoretical Computer Science
Steady-state MSE performance analysis of mixture approaches to adaptive filtering
IEEE Transactions on Signal Processing
Approximation algorithms for restless bandit problems
Journal of the ACM (JACM)
Sharp dichotomies for regret minimization in metric spaces
SODA '10 Proceedings of the twenty-first annual ACM-SIAM symposium on Discrete Algorithms
Algorithms and theory of computation handbook
Online learning in adversarial Lipschitz environments
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part II
Toward a classification of finite partial-monitoring games
ALT'10 Proceedings of the 21st international conference on Algorithmic learning theory
Regret Bounds and Minimax Policies under Partial Monitoring
The Journal of Machine Learning Research
Meta optimization and its application to portfolio selection
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Ensembles and multiple classifiers: a game-theoretic view
MCS'11 Proceedings of the 10th international conference on Multiple classifier systems
Relative loss bounds for on-line density estimation with the exponential family of distributions
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Risk-Sensitive online learning
ALT'06 Proceedings of the 17th international conference on Algorithmic Learning Theory
Hannan consistency in on-line learning in case of unbounded losses under partial monitoring
ALT'06 Proceedings of the 17th international conference on Algorithmic Learning Theory
STACS'06 Proceedings of the 23rd Annual conference on Theoretical Aspects of Computer Science
On following the perturbed leader in the bandit setting
ALT'05 Proceedings of the 16th international conference on Algorithmic Learning Theory
ALT'05 Proceedings of the 16th international conference on Algorithmic Learning Theory
Non-asymptotic calibration and resolution
ALT'05 Proceedings of the 16th international conference on Algorithmic Learning Theory
Defensive prediction with expert advice
ALT'05 Proceedings of the 16th international conference on Algorithmic Learning Theory
A randomized online learning algorithm for better variance control
COLT'06 Proceedings of the 19th annual conference on Learning Theory
The shortest path problem under partial monitoring
COLT'06 Proceedings of the 19th annual conference on Learning Theory
Continuous experts and the binning algorithm
COLT'06 Proceedings of the 19th annual conference on Learning Theory
Aggregating strategy for online auctions
COCOON'06 Proceedings of the 12th annual international conference on Computing and Combinatorics
The weak aggregating algorithm and weak mixability
COLT'05 Proceedings of the 18th annual conference on Learning Theory
Tracking the best of many experts
COLT'05 Proceedings of the 18th annual conference on Learning Theory
Improved second-order bounds for prediction with expert advice
COLT'05 Proceedings of the 18th annual conference on Learning Theory
Trading in markovian price models
COLT'05 Proceedings of the 18th annual conference on Learning Theory
Dynamic cooperator selection in cognitive radio networks
Ad Hoc Networks
A learning-based approach to reactive security
FC'10 Proceedings of the 14th international conference on Financial Cryptography and Data Security
Automatic categorization of patent applications using classifier combinations
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
Sparse regression learning by aggregation and Langevin Monte-Carlo
Journal of Computer and System Sciences
Learning with stochastic inputs and adversarial outputs
Journal of Computer and System Sciences
Linear programming with online learning
Operations Research Letters
Minmax regret solutions for minimax optimization problems with uncertainty
Operations Research Letters
Confidence-weighted linear classification for text categorization
The Journal of Machine Learning Research
Adaptive mixture methods based on Bregman divergences
Digital Signal Processing
Tighter PAC-Bayes bounds through distribution-dependent priors
Theoretical Computer Science
Toward a classification of finite partial-monitoring games
Theoretical Computer Science
Adaptive regularization of weight vectors
Machine Learning
Truthful incentives in crowdsourcing tasks using regret minimization mechanisms
Proceedings of the 22nd international conference on World Wide Web
Lower bounds and selectivity of weak-consistent policies in stochastic multi-armed bandit problem
The Journal of Machine Learning Research
ASC: automatically scalable computation
Proceedings of the 19th international conference on Architectural support for programming languages and operating systems
Combining initial segments of lists
Theoretical Computer Science
An ensemble-clustering-based distance metric and its applications
International Journal of Business Intelligence and Data Mining
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We analyze algorithms that predict a binary value by combining the predictions of several prediction strategies, called experts. Our analysis is for worst-case situations, i.e., we make no assumptions about the way the sequence of bits to be predicted is generated. We measure the performance of the algorithm by the difference between the expected number of mistakes it makes on the bit sequence and the expected number of mistakes made by the best expert on this sequence, where the expectation is taken with respect to the randomization in the predictins. We show that the minimum achievable difference is on the order of the square root of the number of mistakes of the best expert, and we give efficient algorithms that achieve this. Our upper and lower bounds have matching leading constants in most cases. We then show how this leads to certain kinds of pattern recognition/learning algorithms with performance bounds that improve on the best results currently know in this context. We also compare our analysis to the case in which log loss is used instead of the expected number of mistakes.