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Convex Optimization

589 directly classified papers

Papers per year

Papers

Generalized Conditional Gradient for Sparse Estimation JMLR 2017
Optimized Pre-Processing for Discrimination Prevention NIPS 2017
Limitations on Variance-Reduction and Acceleration Schemes for Finite Sums Optimization NIPS 2017
Geometric Descent Method for Convex Composite Minimization NIPS 2017
A New Alternating Direction Method for Linear Programming NIPS 2017
Online to Offline Conversions, Universality and Adaptive Minibatch Sizes NIPS 2017
Large-Scale Quadratically Constrained Quadratic Program via Low-Discrepancy Sequences NIPS 2017
Distributed Accelerated Proximal Coordinate Gradient Methods IJCAI 2017
Fast Rates for Bandit Optimization with Upper-Confidence Frank-Wolfe NIPS 2017
Convex Phase Retrieval without Lifting via PhaseMax ICML 2017
SVD-free Convex-Concave Approaches for Nuclear Norm Regularization IJCAI 2017
Exploiting Strong Convexity from Data with Primal-Dual First-Order Algorithms ICML 2017
Optimal Algorithms for Smooth and Strongly Convex Distributed Optimization in Networks ICML 2017
Clustering by Sum of Norms: Stochastic Incremental Algorithm, Convergence and Cluster Recovery ICML 2017
A Semismooth Newton Method for Fast, Generic Convex Programming ICML 2017
Frame-based Data Factorizations ICML 2017
Active-set Methods for Submodular Minimization Problems JMLR 2017
Faster Convex Optimization: Simulated Annealing with an Efficient Universal Barrier ICML 2016
An equivalence between high dimensional Bayes optimal inference and M-estimation NIPS 2016
Stochastic Variance Reduction Methods for Saddle-Point Problems NIPS 2016
Structure-Blind Signal Recovery NIPS 2016
The non-convex Burer-Monteiro approach works on smooth semidefinite programs NIPS 2016
Asynchronous Parallel Greedy Coordinate Descent NIPS 2016
SDP Relaxation with Randomized Rounding for Energy Disaggregation NIPS 2016
A Simple Practical Accelerated Method for Finite Sums NIPS 2016