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Optimization

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Papers

Sequence to Better Sequence: Continuous Revision of Combinatorial Structures ICML 2017
Variants of RMSProp and Adagrad with Logarithmic Regret Bounds ICML 2017
SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient ICML 2017
The Statistical Recurrent Unit ICML 2017
Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability ICML 2017
Online and Linear-Time Attention by Enforcing Monotonic Alignments ICML 2017
High Dimensional Bayesian Optimization with Elastic Gaussian Process ICML 2017
Large-Scale Evolution of Image Classifiers ICML 2017
Parallel Multiscale Autoregressive Density Estimation ICML 2017
Failures of Gradient-Based Deep Learning ICML 2017
Orthogonalized ALS: A Theoretically Principled Tensor Decomposition Algorithm for Practical Use ICML 2017
On the Iteration Complexity of Support Recovery via Hard Thresholding Pursuit ICML 2017
Gradient Boosted Decision Trees for High Dimensional Sparse Output ICML 2017
Probabilistic Submodular Maximization in Sub-Linear Time ICML 2017
Gradient Projection Iterative Sketch for Large-Scale Constrained Least-Squares ICML 2017
Stochastic DCA for the Large-sum of Non-convex Functions Problem and its Application to Group Variable Selection in Classification ICML 2017
Boosted Fitted Q-Iteration ICML 2017
Breaking Locality Accelerates Block Gauss-Seidel ICML 2017
Sketched Ridge Regression: Optimization Perspective, Statistical Perspective, and Model Averaging ICML 2017
Efficient Distributed Learning with Sparsity ICML 2017
Variational Policy for Guiding Point Processes ICML 2017
Exploiting Strong Convexity from Data with Primal-Dual First-Order Algorithms ICML 2017
A Unified Variance Reduction-Based Framework for Nonconvex Low-Rank Matrix Recovery ICML 2017
Unifying Task Specification in Reinforcement Learning ICML 2017
Learning Latent Space Models with Angular Constraints ICML 2017