sample complexity

Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization NeurIPS 2018 Do Outliers Ruin Collaboration? ICML 2018 Empirical Risk Minimization in Non-interactive Local Differential Privacy Revisited NeurIPS 2018 Entropy Rate Estimation for Markov Chains with Large State Space NeurIPS 2018 Fast and Sample Efficient Inductive Matrix Completion via Multi-Phase Procrustes Flow ICML 2018 Fast and Sample Near-Optimal Algorithms for Learning Multidimensional Histograms COLT 2018 Feedback-Based Tree Search for Reinforcement Learning ICML 2018 Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers ICML 2018 How Many Samples are Needed to Estimate a Convolutional Neural Network? NeurIPS 2018 Improved Algorithms for Collaborative PAC Learning NeurIPS 2018 INSPECTRE: Privately Estimating the Unseen ICML 2018 Learners that Use Little Information ALT 2018 Learning Compact Neural Networks with Regularization ICML 2018 Learning Diffusion using Hyperparameters ICML 2018 Learning from Group Comparisons: Exploiting Higher Order Interactions NeurIPS 2018 Learning linear structural equation models in polynomial time and sample complexity AISTATS 2018 Learning Mixtures of Linear Regressions with Nearly Optimal Complexity COLT 2018 Learning Single-Index Models in Gaussian Space COLT 2018 Learning Sparse Polymatrix Games in Polynomial Time and Sample Complexity AISTATS 2018 Learning without the Phase: Regularized PhaseMax Achieves Optimal Sample Complexity NeurIPS 2018 Least-Squares Temporal Difference Learning for the Linear Quadratic Regulator ICML 2018 Locally Private Hypothesis Testing ICML 2018 Minimax Estimation of Neural Net Distance NeurIPS 2018 Model-Agnostic Private Learning NeurIPS 2018 Model-Ensemble Trust-Region Policy Optimization ICLR 2018