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Learning Theory

5312 directly classified papers

Papers per year

Papers

Bundle Methods for Machine Learning NIPS 2007
Transfer Learning using Kolmogorov Complexity: Basic Theory and Empirical Evaluations NIPS 2007
Selecting Observations against Adversarial Objectives NIPS 2007
Progressive mixture rules are deviation suboptimal NIPS 2007
Separating Models of Learning from Correlated and Uncorrelated Data JMLR 2007
Learnability of Gaussians with Flexible Variances JMLR 2007
Computational Equivalence of Fixed Points and No Regret Algorithms, and Convergence to Equilibria NIPS 2007
Boosting the Area under the ROC Curve NIPS 2007
The Value of Labeled and Unlabeled Examples when the Model is Imperfect NIPS 2007
Regret Minimization in Games with Incomplete Information NIPS 2007
The Tradeoffs of Large Scale Learning NIPS 2007
Catching Up Faster in Bayesian Model Selection and Model Averaging NIPS 2007
Learning Bounds for Domain Adaptation NIPS 2007
The Epoch-Greedy Algorithm for Multi-armed Bandits with Side Information NIPS 2007
Cluster Stability for Finite Samples NIPS 2007
Stability Bounds for Non-i.i.d. Processes NIPS 2007
A general agnostic active learning algorithm NIPS 2007
An Oracle Inequality for Clipped Regularized Risk Minimizers NIPS 2006
Logarithmic Online Regret Bounds for Undiscounted Reinforcement Learning NIPS 2006
AdaBoost is Consistent NIPS 2006
Tighter PAC-Bayes Bounds NIPS 2006
On the Complexity of Learning Lexicographic Strategies JMLR 2006
A Robust Procedure For Gaussian Graphical Model Search From Microarray Data With p Larger Than n JMLR 2006
Stability Properties of Empirical Risk Minimization over Donsker Classes JMLR 2006
On Model Selection Consistency of Lasso JMLR 2006