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Learning Theory

5,312 papers

Papers per year

Papers

Incorporating Label Dependencies in Multilabel Stance Detection EMNLP 2019
Big Generalizations with Small Data: Exploring the Role of Training Samples in Learning Adjectives of Size EMNLP 2019
On Network Design Spaces for Visual Recognition ICCV 2019
How Do Neural Networks See Depth in Single Images? ICCV 2019
PAC Learnability of Node Functions in Networked Dynamical Systems ICML 2019
A Convergence Theory for Deep Learning via Over-Parameterization ICML 2019
Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks ICML 2019
Correlated bandits or: How to minimize mean-squared error online ICML 2019
Target Tracking for Contextual Bandits: Application to Demand Side Management ICML 2019
Why do Larger Models Generalize Better? A Theoretical Perspective via the XOR Problem ICML 2019
Adversarial examples from computational constraints ICML 2019
PAC Identification of Many Good Arms in Stochastic Multi-Armed Bandits ICML 2019
New results on information theoretic clustering ICML 2019
Policy Certificates: Towards Accountable Reinforcement Learning ICML 2019
Learning-to-Learn Stochastic Gradient Descent with Biased Regularization ICML 2019
Finite-Time Analysis of Distributed TD(0) with Linear Function Approximation on Multi-Agent Reinforcement Learning ICML 2019
Generalized No Free Lunch Theorem for Adversarial Robustness ICML 2019
Width Provably Matters in Optimization for Deep Linear Neural Networks ICML 2019
The advantages of multiple classes for reducing overfitting from test set reuse ICML 2019
The information-theoretic value of unlabeled data in semi-supervised learning ICML 2019
Complexity of Linear Regions in Deep Networks ICML 2019
Random Shuffling Beats SGD after Finite Epochs ICML 2019
Graph Resistance and Learning from Pairwise Comparisons ICML 2019
Better generalization with less data using robust gradient descent ICML 2019
Bilinear Bandits with Low-rank Structure ICML 2019