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Learning Theory

5,334 papers

Papers per year

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123
466
307
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Papers

Causal Bandits: Learning Good Interventions via Causal Inference NIPS 2016
Theoretical Comparisons of Positive-Unlabeled Learning against Positive-Negative Learning NIPS 2016
Sample Complexity of Automated Mechanism Design NIPS 2016
The Power of Optimization from Samples NIPS 2016
Mistake Bounds for Binary Matrix Completion NIPS 2016
Quantum Perceptron Models NIPS 2016
Average-case hardness of RIP certification NIPS 2016
Combining Adversarial Guarantees and Stochastic Fast Rates in Online Learning NIPS 2016
Learning Kernels with Random Features NIPS 2016
Combinatorial semi-bandit with known covariance NIPS 2016
Deep Learning without Poor Local Minima NIPS 2016
Parameter-Free Convex Learning through Coin Betting AUTOML 2016
Learning from Survey Training Samples: Rate Bounds for Horvitz-Thompson Risk Minimizers ACML 2016
Learnability of Non-I.I.D. ACML 2016
No Regret Bound for Extreme Bandits AISTATS 2016
Nearly Optimal Classification for Semimetrics AISTATS 2016
PAC-Bayesian Bounds based on the Rényi Divergence AISTATS 2016
Graph Connectivity in Noisy Sparse Subspace Clustering AISTATS 2016
Online Learning with Noisy Side Observations AISTATS 2016
Controlling Bias in Adaptive Data Analysis Using Information Theory AISTATS 2016
Loss Bounds and Time Complexity for Speed Priors AISTATS 2016
Representation and Learning of Temporal Relations COLING 2016
Open Problem: Best Arm Identification: Almost Instance-Wise Optimality and the Gap Entropy Conjecture COLT 2016
Open Problem: Second order regret bounds based on scaling time COLT 2016
Sign rank versus VC dimension COLT 2016