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

Optimization

14,983 papers

Papers per year

18
112
342
1289
1646
'05
'10
'15
'20
'25

Papers

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
Combinatorial Multi-Armed Bandit with General Reward Functions NIPS 2016
SEBOOST - Boosting Stochastic Learning Using Subspace Optimization Techniques NIPS 2016
Multistage Campaigning in Social Networks NIPS 2016
Global Optimality of Local Search for Low Rank Matrix Recovery NIPS 2016
Optimistic Bandit Convex Optimization NIPS 2016
Minimax Optimal Alternating Minimization for Kernel Nonparametric Tensor Learning NIPS 2016
Homotopy Smoothing for Non-Smooth Problems with Lower Complexity than $O(1/\epsilon)$ NIPS 2016
Fast Algorithms for Robust PCA via Gradient Descent NIPS 2016
Dimensionality Reduction of Massive Sparse Datasets Using Coresets NIPS 2016
Doubly Convolutional Neural Networks NIPS 2016
Local Minimax Complexity of Stochastic Convex Optimization NIPS 2016
Normalized Spectral Map Synchronization NIPS 2016
Regularized Nonlinear Acceleration NIPS 2016
Stochastic Online AUC Maximization NIPS 2016
Optimizing affinity-based binary hashing using auxiliary coordinates NIPS 2016
Without-Replacement Sampling for Stochastic Gradient Methods NIPS 2016