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Learning Theory

5,334 papers

Papers per year

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123
466
307
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Papers

Refined Lower Bounds for Adversarial Bandits NIPS 2016
A Constant-Factor Bi-Criteria Approximation Guarantee for k-means++ NIPS 2016
Multi-step learning and underlying structure in statistical models NIPS 2016
Tracking the Best Expert in Non-stationary Stochastic Environments NIPS 2016
Regret of Queueing Bandits NIPS 2016
Finite Sample Prediction and Recovery Bounds for Ordinal Embedding NIPS 2016
Minimax Estimation of Maximum Mean Discrepancy with Radial Kernels NIPS 2016
Following the Leader and Fast Rates in Linear Prediction: Curved Constraint Sets and Other Regularities NIPS 2016
More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised Learning NIPS 2016
Only H is left: Near-tight Episodic PAC RL NIPS 2016
Fast learning rates with heavy-tailed losses NIPS 2016
Tight Complexity Bounds for Optimizing Composite Objectives NIPS 2016
On the Recursive Teaching Dimension of VC Classes NIPS 2016
Boosting with Abstention NIPS 2016
Robustness of classifiers: from adversarial to random noise NIPS 2016
Learning Bound for Parameter Transfer Learning NIPS 2016
PAC-Bayesian Theory Meets Bayesian Inference NIPS 2016
A Consistent Regularization Approach for Structured Prediction NIPS 2016
Generalization of ERM in Stochastic Convex Optimization: The Dimension Strikes Back NIPS 2016
The Limits of Learning with Missing Data NIPS 2016
Blind Attacks on Machine Learners NIPS 2016
Toward Deeper Understanding of Neural Networks: The Power of Initialization and a Dual View on Expressivity NIPS 2016
Global Optimality of Local Search for Low Rank Matrix Recovery NIPS 2016
Optimistic Bandit Convex Optimization NIPS 2016
Learning in Games: Robustness of Fast Convergence NIPS 2016