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Learning Theory

5312 directly classified papers

Papers per year

Papers

The Blinded Bandit: Learning with Adaptive Feedback NIPS 2014
Quantized Estimation of Gaussian Sequence Models in Euclidean Balls NIPS 2014
Optimizing F-Measures by Cost-Sensitive Classification NIPS 2014
Efficient Partial Monitoring with Prior Information NIPS 2014
Learning the Learning Rate for Prediction with Expert Advice NIPS 2014
Making Pairwise Binary Graphical Models Attractive NIPS 2014
Lower Bounds on the Performance of Polynomial-time Algorithms for Sparse Linear Regression COLT 2014
Localized Complexities for Transductive Learning COLT 2014
The sample complexity of agnostic learning under deterministic labels COLT 2014
A second-order bound with excess losses COLT 2014
Learning without concentration COLT 2014
Distribution-independent Reliable Learning COLT 2014
Open Problem: The Statistical Query Complexity of Learning Sparse Halfspaces COLT 2014
Efficient Sampling for Learning Sparse Additive Models in High Dimensions NIPS 2014
Spectral Methods meet EM: A Provably Optimal Algorithm for Crowdsourcing NIPS 2014
Follow the Leader If You Can, Hedge If You Must JMLR 2014
How hard is my MDP?" The distribution-norm to the rescue" NIPS 2014
Bias in Natural Actor-Critic Algorithms ICML 2014
Surrogate Regret Bounds for Bipartite Ranking via Strongly Proper Losses JMLR 2014
Active Learning Using Smooth Relative Regret Approximations with Applications JMLR 2014
Narrowing the Gap: Random Forests In Theory and In Practice ICML 2014
How transferable are features in deep neural networks? NIPS 2014
Optimistic Planning in Markov Decision Processes Using a Generative Model NIPS 2014
Sparse Multi-Task Reinforcement Learning NIPS 2014
Learning Shuffle Ideals Under Restricted Distributions NIPS 2014