conftrace_
← Optimization & Theory
Machine Learning › Optimization & Theory ›

Learning Theory

5,312 papers

Papers per year

Papers

On Learning Markov Chains NIPS 2018
Is Q-Learning Provably Efficient? NIPS 2018
Exploration in Structured Reinforcement Learning NIPS 2018
How to Start Training: The Effect of Initialization and Architecture NIPS 2018
On the Local Minima of the Empirical Risk NIPS 2018
Minimax Estimation of Neural Net Distance NIPS 2018
Overfitting or perfect fitting? Risk bounds for classification and regression rules that interpolate NIPS 2018
Tight Bounds for Collaborative PAC Learning via Multiplicative Weights NIPS 2018
Learning latent variable structured prediction models with Gaussian perturbations NIPS 2018
Context-dependent upper-confidence bounds for directed exploration NIPS 2018
Adversarially Robust Generalization Requires More Data NIPS 2018
Modern Neural Networks Generalize on Small Data Sets NIPS 2018
PAC-Bayes Control: Synthesizing Controllers that Provably Generalize to Novel Environments CORL 2018
LSTMs Can Learn Syntax-Sensitive Dependencies Well, But Modeling Structure Makes Them Better ACL 2018
Predicting accuracy on large datasets from smaller pilot data ACL 2018
On the Practical Computational Power of Finite Precision RNNs for Language Recognition ACL 2018
On the Impact of Various Types of Noise on Neural Machine Translation ACL 2018
LSTMs Exploit Linguistic Attributes of Data ACL 2018
On how complexity affects the stability of a predictor AISTATS 2018
Discriminative Learning of Prediction Intervals AISTATS 2018
Optimal Cooperative Inference AISTATS 2018
Tensor Regression Meets Gaussian Processes AISTATS 2018
Regional Multi-Armed Bandits AISTATS 2018
Nearly second-order optimality of online joint detection and estimation via one-sample update schemes AISTATS 2018
Contextual Bandits with Stochastic Experts AISTATS 2018