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Continuous Optimization

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Nesterov's Acceleration for Approximate Newton JMLR 2020
apricot: Submodular selection for data summarization in Python JMLR 2020
Universal Average-Case Optimality of Polyak Momentum ICML 2020
Lower Complexity Bounds for Finite-Sum Convex-Concave Minimax Optimization Problems ICML 2020
Partial Optimal Tranport with applications on Positive-Unlabeled Learning NIPS 2020
Safe screening rules for L0-regression from Perspective Relaxations ICML 2020
DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian Networks NIPS 2020
On Convergence of Distributed Approximate Newton Methods: Globalization, Sharper Bounds and Beyond JMLR 2020
Tight Approximation for Proportional Approval Voting IJCAI 2020
Sufficient dimension reduction for classification using principal optimal transport direction NIPS 2020
Fast Epigraphical Projection-based Incremental Algorithms for Wasserstein Distributionally Robust Support Vector Machine NIPS 2020
Adaptive Reduced Rank Regression NIPS 2020
Sequential Bayesian Experimental Design with Variable Cost Structure NIPS 2020
Sparse Convex Optimization via Adaptively Regularized Hard Thresholding ICML 2020
Boosting Frank-Wolfe by Chasing Gradients ICML 2020
Inexact Tensor Methods with Dynamic Accuracies ICML 2020
Self-Concordant Analysis of Frank-Wolfe Algorithms ICML 2020
Ridge Rider: Finding Diverse Solutions by Following Eigenvectors of the Hessian NIPS 2020
Adaptive Sketching for Fast and Convergent Canonical Polyadic Decomposition ICML 2020
pbSGD: Powered Stochastic Gradient Descent Methods for Accelerated Non-Convex Optimization IJCAI 2020
Parabolic Approximation Line Search for DNNs NIPS 2020
Greedy Convex Ensemble IJCAI 2020
Non-monotone DR-submodular Maximization over General Convex Sets IJCAI 2020
Learning With Subquadratic Regularization : A Primal-Dual Approach IJCAI 2020
Training Generative Adversarial Networks by Solving Ordinary Differential Equations NIPS 2020