Mistake bounds and logarithmic linear-threshold learning algorithms
Mistake bounds and logarithmic linear-threshold learning algorithms
COLT '90 Proceedings of the third annual workshop on Computational learning theory
The weighted majority algorithm
Information and Computation
Using experts for predicting continuous outcomes
Euro-COLT '93 Proceedings of the first European conference on Computational learning theory
A game of prediction with expert advice
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
A dynamic disk spin-down technique for mobile computing
MobiCom '96 Proceedings of the 2nd annual international conference on Mobile computing and networking
Exponentiated gradient versus gradient descent for linear predictors
Information and Computation
A decision-theoretic generalization of on-line learning and an application to boosting
Journal of Computer and System Sciences - Special issue: 26th annual ACM symposium on the theory of computing & STOC'94, May 23–25, 1994, and second annual Europe an conference on computational learning theory (EuroCOLT'95), March 13–15, 1995
Derandomizing stochastic prediction strategies
COLT '97 Proceedings of the tenth annual conference on Computational learning theory
On-line learning and the metrical task system problem
COLT '97 Proceedings of the tenth annual conference on Computational learning theory
General convergence results for linear discriminant updates
COLT '97 Proceedings of the tenth annual conference on Computational learning theory
The binary exponentiated gradient algorithm for learning linear functions
COLT '97 Proceedings of the tenth 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
Relative loss bounds for multidimensional regression problems
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Worst-case quadratic loss bounds for prediction using linear functions and gradient descent
IEEE Transactions on Neural Networks
The complexity of learning according to two models of a drifting environment
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
The robustness of the p-norm algorithms
COLT '99 Proceedings of the twelfth annual conference on Computational learning theory
Additive models, boosting, and inference for generalized divergences
COLT '99 Proceedings of the twelfth annual conference on Computational learning theory
Boosting as entropy projection
COLT '99 Proceedings of the twelfth annual conference on Computational learning theory
The Complexity of Learning According to Two Models of a Drifting Environment
Machine Learning - The Eleventh Annual Conference on computational Learning Theory
Relative Loss Bounds for Temporal-Difference Learning
Machine Learning
On-Line Estimation of Hidden Markov Model Parameters
DS '00 Proceedings of the Third International Conference on Discovery Science
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
Learning Additive Models Online with Fast Evaluating Kernels
COLT '01/EuroCOLT '01 Proceedings of the 14th Annual Conference on Computational Learning Theory and and 5th European Conference on Computational Learning Theory
Tracking the best linear predictor
The Journal of Machine Learning Research
The Robustness of the p-Norm Algorithms
Machine Learning
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
Intrinsic Geometries in Learning
Emerging Trends in Visual Computing
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
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