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Optimization

14,207 papers

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Papers

Large-Scale Quadratically Constrained Quadratic Program via Low-Discrepancy Sequences NIPS 2017
Graph Matching via Multiplicative Update Algorithm NIPS 2017
Subset Selection under Noise NIPS 2017
Compression-aware Training of Deep Networks NIPS 2017
Practical Bayesian Optimization for Model Fitting with Bayesian Adaptive Direct Search NIPS 2017
Multi-Information Source Optimization NIPS 2017
Learning ReLUs via Gradient Descent NIPS 2017
Efficient Use of Limited-Memory Accelerators for Linear Learning on Heterogeneous Systems NIPS 2017
Stochastic Mirror Descent in Variationally Coherent Optimization Problems NIPS 2017
Polynomial Codes: an Optimal Design for High-Dimensional Coded Matrix Multiplication NIPS 2017
Hierarchical Clustering Beyond the Worst-Case NIPS 2017
ADMM without a Fixed Penalty Parameter: Faster Convergence with New Adaptive Penalization NIPS 2017
Adaptive Batch Size for Safe Policy Gradients NIPS 2017
REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models NIPS 2017
An inner-loop free solution to inverse problems using deep neural networks NIPS 2017
Differentially Private Empirical Risk Minimization Revisited: Faster and More General NIPS 2017
Wasserstein Learning of Deep Generative Point Process Models NIPS 2017
Machine Learning with Adversaries: Byzantine Tolerant Gradient Descent NIPS 2017
Alternating Estimation for Structured High-Dimensional Multi-Response Models NIPS 2017
Generative Local Metric Learning for Kernel Regression NIPS 2017
Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent NIPS 2017
Gradient Descent Can Take Exponential Time to Escape Saddle Points NIPS 2017
Asynchronous Coordinate Descent under More Realistic Assumptions NIPS 2017
Balancing information exposure in social networks NIPS 2017
Nonlinear Acceleration of Stochastic Algorithms NIPS 2017