Optimization

Non-Convex Projected Gradient Descent for Generalized Low-Rank Tensor Regression JMLR 2019 Nonconvex Variance Reduced Optimization with Arbitrary Sampling ICML 2019 Non-Ergodic Convergence Analysis of Heavy-Ball Algorithms AAAI 2019 Nonlinear Acceleration of Primal-Dual Algorithms AISTATS 2019 Non-Parametric Priors For Generative Adversarial Networks ICML 2019 NOODL: Provable Online Dictionary Learning and Sparse Coding ICLR 2019 No Pressure! Addressing the Problem of Local Minima in Manifold Learning Algorithms NeurIPS 2019 No-Regret Bayesian Optimization with Unknown Hyperparameters JMLR 2019 Normalized Wasserstein for Mixture Distributions With Applications in Adversarial Learning and Domain Adaptation ICCV 2019 Numerically Accurate Hyperbolic Embeddings Using Tiling-Based Models NeurIPS 2019 Numerical Optimization to AI, and Back AAAI 2019 ODE-Inspired Network Design for Single Image Super-Resolution CVPR 2019 On Certifying Non-Uniform Bounds against Adversarial Attacks ICML 2019 On Computation and Generalization of Generative Adversarial Networks under Spectrum Control ICLR 2019 On Constrained Nonconvex Stochastic Optimization: A Case Study for Generalized Eigenvalue Decomposition AISTATS 2019 On Densification for Minwise Hashing UAI 2019 On Division Versus Saturation in Pseudo-Boolean Solving IJCAI 2019 On Efficient Retrieval of Top Similarity Vectors EMNLP 2019 On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don’t Worry About its Nonsmooth Loss Function UAI 2019 On Implicit Filter Level Sparsity in Convolutional Neural Networks CVPR 2019 On Lazy Training in Differentiable Programming NeurIPS 2019 Online Continual Learning with Maximal Interfered Retrieval NeurIPS 2019 Online Convex Matrix Factorization with Representative Regions NeurIPS 2019 Online Convex Optimization for Sequential Decision Processes and Extensive-Form Games AAAI 2019 Online Convex Optimization in Adversarial Markov Decision Processes ICML 2019