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Learning Theory

5312 directly classified papers

Papers per year

Papers

A New Look at Nearest Neighbours: Identifying Benign Input Geometries via Random Projections ACML 2015
Tradeoffs for Space, Time, Data and Risk in Unsupervised Learning AISTATS 2015
Bandit Convex Optimization: \sqrtT Regret in One Dimension COLT 2015
How Hard is Inference for Structured Prediction? ICML 2015
Open Problem: Learning Quantum Circuits with Queries COLT 2015
Learning with Square Loss: Localization through Offset Rademacher Complexity COLT 2015
Regret Lower Bound and Optimal Algorithm in Dueling Bandit Problem COLT 2015
The Sample Complexity of Learning Linear Predictors with the Squared Loss JMLR 2015
A Chaining Algorithm for Online Nonparametric Regression COLT 2015
Variable Selection is Hard COLT 2015
Learning and inference in the presence of corrupted inputs COLT 2015
On the Complexity of Learning with Kernels COLT 2015
Bad Universal Priors and Notions of Optimality COLT 2015
Structural Maxent Models ICML 2015
Ranking from Stochastic Pairwise Preferences: Recovering Condorcet Winners and Tournament Solution Sets at the Top ICML 2015
Towards a Lower Sample Complexity for Robust One-bit Compressed Sensing ICML 2015
Counterfactual Risk Minimization: Learning from Logged Bandit Feedback ICML 2015
The Hedge Algorithm on a Continuum ICML 2015
Simple regret for infinitely many armed bandits ICML 2015
Optimal Regret Analysis of Thompson Sampling in Stochastic Multi-armed Bandit Problem with Multiple Plays ICML 2015
Strongly Adaptive Online Learning ICML 2015
Risk and Regret of Hierarchical Bayesian Learners ICML 2015
Towards a Learning Theory of Cause-Effect Inference ICML 2015
K-hyperplane Hinge-Minimax Classifier ICML 2015
On the Optimality of Multi-Label Classification under Subset Zero-One Loss for Distributions Satisfying the Composition Property ICML 2015