Learning Theory

Optimistic Planning in Markov Decision Processes Using a Generative Model NeurIPS 2014 Optimizing F-Measures by Cost-Sensitive Classification NeurIPS 2014 Orbit Regularization NeurIPS 2014 PAC-Bayesian Collective Stability AISTATS 2014 PAC-Bayesian Theory for Transductive Learning AISTATS 2014 PAC-inspired Option Discovery in Lifelong Reinforcement Learning ICML 2014 Probably Approximately Correct MDP Learning and Control With Temporal Logic Constraints RSS 2014 Provable Bounds for Learning Some Deep Representations ICML 2014 Pursuit-Evasion Without Regret, with an Application to Trading ICML 2014 Quantized Estimation of Gaussian Sequence Models in Euclidean Balls NeurIPS 2014 QUIC & DIRTY: A Quadratic Approximation Approach for Dirty Statistical Models NeurIPS 2014 Rates of Convergence for Nearest Neighbor Classification NeurIPS 2014 Recursive Teaching Dimension, VC-Dimension and Sample Compression JMLR 2014 Reducing Dueling Bandits to Cardinal Bandits ICML 2014 Relative Upper Confidence Bound for the K-Armed Dueling Bandit Problem ICML 2014 Sample Complexity Bounds on Differentially Private Learning via Communication Complexity COLT 2014 Sample Compression for Multi-label Concept Classes COLT 2014 Selective Sampling with Drift AISTATS 2014 Skip Context Tree Switching ICML 2014 Sparse Multi-Task Reinforcement Learning NeurIPS 2014 Sparse Polynomial Learning and Graph Sketching NeurIPS 2014 Spectral Methods meet EM: A Provably Optimal Algorithm for Crowdsourcing NeurIPS 2014 Stochastic Multi-Armed-Bandit Problem with Non-stationary Rewards NeurIPS 2014 Subspace Embeddings for the Polynomial Kernel NeurIPS 2014 Surrogate Regret Bounds for Bipartite Ranking via Strongly Proper Losses JMLR 2014