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Optimization

14,207 papers

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Papers

Dynamic matrix recovery from incomplete observations under an exact low-rank constraint NIPS 2016
Tight Complexity Bounds for Optimizing Composite Objectives NIPS 2016
Verification Based Solution for Structured MAB Problems NIPS 2016
Computing and maximizing influence in linear threshold and triggering models NIPS 2016
Wasserstein Training of Restricted Boltzmann Machines NIPS 2016
Global Analysis of Expectation Maximization for Mixtures of Two Gaussians NIPS 2016
Stochastic Structured Prediction under Bandit Feedback NIPS 2016
A Minimax Approach to Supervised Learning NIPS 2016
Blazing the trails before beating the path: Sample-efficient Monte-Carlo planning NIPS 2016
Matrix Completion has No Spurious Local Minimum NIPS 2016
Deep Submodular Functions: Definitions and Learning NIPS 2016
Fast recovery from a union of subspaces NIPS 2016
Structured Sparse Regression via Greedy Hard Thresholding NIPS 2016
A Multi-Batch L-BFGS Method for Machine Learning NIPS 2016
Gradient-based Sampling: An Adaptive Importance Sampling for Least-squares NIPS 2016
Accelerating Stochastic Composition Optimization NIPS 2016
Measuring Neural Net Robustness with Constraints NIPS 2016
Safe Policy Improvement by Minimizing Robust Baseline Regret NIPS 2016
On Regularizing Rademacher Observation Losses NIPS 2016
High-Rank Matrix Completion and Clustering under Self-Expressive Models NIPS 2016
Adaptive Newton Method for Empirical Risk Minimization to Statistical Accuracy NIPS 2016
Batched Gaussian Process Bandit Optimization via Determinantal Point Processes NIPS 2016
Scalable Adaptive Stochastic Optimization Using Random Projections NIPS 2016
Solving Marginal MAP Problems with NP Oracles and Parity Constraints NIPS 2016
Adaptive Smoothed Online Multi-Task Learning NIPS 2016