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Learning Theory

5,312 papers

Papers per year

Papers

When do random forests fail? NIPS 2018
Learning convex polytopes with margin NIPS 2018
Adaptation to Easy Data in Prediction with Limited Advice NIPS 2018
A Smoothed Analysis of the Greedy Algorithm for the Linear Contextual Bandit Problem NIPS 2018
Adversarial Risk and Robustness: General Definitions and Implications for the Uniform Distribution NIPS 2018
Improved Algorithms for Collaborative PAC Learning NIPS 2018
PAC-Bayes bounds for stable algorithms with instance-dependent priors NIPS 2018
Quantifying Learning Guarantees for Convex but Inconsistent Surrogates NIPS 2018
Near Optimal Exploration-Exploitation in Non-Communicating Markov Decision Processes NIPS 2018
The Description Length of Deep Learning models NIPS 2018
Contextual Pricing for Lipschitz Buyers NIPS 2018
But How Does It Work in Theory? Linear SVM with Random Features NIPS 2018
Optimization of Smooth Functions with Noisy Observations: Local Minimax Rates NIPS 2018
Bias and Generalization in Deep Generative Models: An Empirical Study NIPS 2018
Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data NIPS 2018
Uniform Convergence of Gradients for Non-Convex Learning and Optimization NIPS 2018
On Oracle-Efficient PAC RL with Rich Observations NIPS 2018
Towards Understanding Learning Representations: To What Extent Do Different Neural Networks Learn the Same Representation NIPS 2018
Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures NIPS 2018
A Theory-Based Evaluation of Nearest Neighbor Models Put Into Practice NIPS 2018
Learning Loop Invariants for Program Verification NIPS 2018
Balanced Policy Evaluation and Learning NIPS 2018
How SGD Selects the Global Minima in Over-parameterized Learning: A Dynamical Stability Perspective NIPS 2018
Regret Bounds for Online Portfolio Selection with a Cardinality Constraint NIPS 2018
Entropy and mutual information in models of deep neural networks NIPS 2018