← Optimization
Mathematics & Optimization › Optimization ›

Optimization

1203 directly classified papers

Papers per year

Papers

Solving Non-smooth Constrained Programs with Lower Complexity than $\mathcal{O}(1/\varepsilon)$: A Primal-Dual Homotopy Smoothing Approach NIPS 2018
Coordinate Descent with Bandit Sampling NIPS 2018
Inexact trust-region algorithms on Riemannian manifolds NIPS 2018
Direct Runge-Kutta Discretization Achieves Acceleration NIPS 2018
Nonparametric Density Estimation under Adversarial Losses NIPS 2018
A Block Coordinate Ascent Algorithm for Mean-Variance Optimization NIPS 2018
Breaking the Span Assumption Yields Fast Finite-Sum Minimization NIPS 2018
A theory on the absence of spurious solutions for nonconvex and nonsmooth optimization NIPS 2018
Learning To Learn Around A Common Mean NIPS 2018
Exploration in Structured Reinforcement Learning NIPS 2018
Stochastic Spectral and Conjugate Descent Methods NIPS 2018
A Simple Proximal Stochastic Gradient Method for Nonsmooth Nonconvex Optimization NIPS 2018
Short-term Sparse Portfolio Optimization Based on Alternating Direction Method of Multipliers JMLR 2018
A New and Flexible Approach to the Analysis of Paired Comparison Data JMLR 2018
Gradient Descent Learns Linear Dynamical Systems JMLR 2018
RSG: Beating Subgradient Method without Smoothness and Strong Convexity JMLR 2018
A Two-Stage Penalized Least Squares Method for Constructing Large Systems of Structural Equations JMLR 2018
Catalyst Acceleration for First-order Convex Optimization: from Theory to Practice JMLR 2018
Gradient Estimation with Simultaneous Perturbation and Compressive Sensing JMLR 2018
Accelerated Spectral Ranking ICML 2018
Geodesic Convolutional Shape Optimization ICML 2018
Riemannian Optimization for Skip-Gram Negative Sampling ACL 2017
Efficient Kernel Selection via Spectral Analysis IJCAI 2017
Temporal Planning for Compilation of Quantum Approximate Optimization Circuits IJCAI 2017
Adaptive Relaxed ADMM: Convergence Theory and Practical Implementation CVPR 2017