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Learning Theory

5312 directly classified papers

Papers per year

Papers

Minimum Conditional Entropy Clustering: A Discriminative Framework for Clustering ACML 2010
Near-optimal Regret Bounds for Reinforcement Learning JMLR 2010
Scrambled Objects for Least-Squares Regression NIPS 2010
Kernel Partial Least Squares is Universally Consistent AISTATS 2010
On the Impact of Kernel Approximation on Learning Accuracy AISTATS 2010
Regret Bounds for Gaussian Process Bandit Problems AISTATS 2010
Negative Results for Active Learning with Convex Losses AISTATS 2010
Learning Exponential Families in High-Dimensions: Strong Convexity and Sparsity AISTATS 2010
Towards Property-Based Classification of Clustering Paradigms NIPS 2010
Closing the Learning-Planning Loop with Predictive State Representations RSS 2010
Why Does Unsupervised Pre-training Help Deep Learning? AISTATS 2010
Impossibility Theorems for Domain Adaptation AISTATS 2010
Regret Bounds and Minimax Policies under Partial Monitoring JMLR 2010
Finite-sample Analysis of Bellman Residual Minimization ACML 2010
Online Learning: Random Averages, Combinatorial Parameters, and Learnability NIPS 2010
Lower Bounds on Rate of Convergence of Cutting Plane Methods NIPS 2010
Agnostic Active Learning Without Constraints NIPS 2010
On Herding and the Perceptron Cycling Theorem NIPS 2010
Supervised Clustering NIPS 2010
Empirical Risk Minimization with Approximations of Probabilistic Grammars NIPS 2010
Trading off Mistakes and Don't-Know Predictions NIPS 2010
Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models NIPS 2010
Identifying Dendritic Processing NIPS 2010
Multi-View Active Learning in the Non-Realizable Case NIPS 2010
Exact learning curves for Gaussian process regression on large random graphs NIPS 2010