Convex Optimization

Robust Policy Synthesis for Uncertain POMDPs via Convex Optimization IJCAI 2020 SAdam: A Variant of Adam for Strongly Convex Functions ICLR 2020 Scalable Calibration of Affinity Matrices from Incomplete Observations ACML 2020 Stochastic Conditional Gradient Methods: From Convex Minimization to Submodular Maximization JMLR 2020 Stochastic Optimization with Heavy-Tailed Noise via Accelerated Gradient Clipping NeurIPS 2020 The Strong Screening Rule for SLOPE NeurIPS 2020 The Wasserstein Proximal Gradient Algorithm NeurIPS 2020 A2BCD: Asynchronous Acceleration with Optimal Complexity ICLR 2019 Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate Message Passing NeurIPS 2019 Analysis of Langevin Monte Carlo via Convex Optimization JMLR 2019 An Embedding Framework for Consistent Polyhedral Surrogates NeurIPS 2019 A Polynomial Time Algorithm for Log-Concave Maximum Likelihood via Locally Exponential Families NeurIPS 2019 A unified variance-reduced accelerated gradient method for convex optimization NeurIPS 2019 A Variational Pan-Sharpening With Local Gradient Constraints CVPR 2019 Calculating Optimistic Likelihoods Using (Geodesically) Convex Optimization NeurIPS 2019 Complexity of Highly Parallel Non-Smooth Convex Optimization NeurIPS 2019 Convex Relaxations for Consensus and Non-Minimal Problems in 3D Vision ICCV 2019 EA-CG: An Approximate Second-Order Method for Training Fully-Connected Neural Networks AAAI 2019 Efficient Algorithms for Smooth Minimax Optimization NeurIPS 2019 Fast and Provable ADMM for Learning with Generative Priors NeurIPS 2019 Fast Decomposable Submodular Function Minimization using Constrained Total Variation NeurIPS 2019 Gaussian Regression with Convex Constraints AISTATS 2019 Globally Convergent Newton Methods for Ill-conditioned Generalized Self-concordant Losses NeurIPS 2019 Hamiltonian descent for composite objectives NeurIPS 2019 Lazifying Conditional Gradient Algorithms JMLR 2019