conftrace_

Optimization

14,850 papers (55 classified directly here)

Subtopics · a paper can sit in several, so these overlap

Continuous Optimization (4,424) Stochastic Methods (2,991) Combinatorial Optimization (2,615) Online Algorithms (2,404) Optimization (1,521) Game Theory (1,046) Convex Optimization (864) Discrete Optimization (721) Optimal Transport (474) Sparse Optimization (416) Optimal Control (271) Global Optimization (200) Non-Convex Optimization (182) Distributed Learning (164) Approximation Algorithms (162) Multi-Objective Optimization (151) Distributed Optimization (136) Bayesian Optimization (132) Theory (109) Compressed Sensing (102) Algorithms (89) Robust Optimization (86) Submodular Optimization (77) Kernel Methods (75) Evolutionary Algorithm (72) Linear Programming (54) Tensor Decomposition (48) Bilevel Optimization (42) Integer Programming (38) Matrix Completion (33) Algorithm (21) Regularization (11)

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Papers (including subtopics)

Stable Intrinsic Auto-Calibration from Fundamental Matrices of Devices with Uncorrelated Camera Parameters WACV 2020 Stable Matchings with Diversity Constraints: Affirmative Action is beyond NP IJCAI 2020 Stable Roommate Problem with Diversity Preferences IJCAI 2020 Stage-wise Conservative Linear Bandits NeurIPS 2020 Stateful Posted Pricing with Vanishing Regret via Dynamic Deterministic Markov Decision Processes NeurIPS 2020 Statistical Efficiency of Thompson Sampling for Combinatorial Semi-Bandits NeurIPS 2020 Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization ICML 2020 Statistical Optimal Transport posed as Learning Kernel Embedding NeurIPS 2020 Stein Self-Repulsive Dynamics: Benefits From Past Samples NeurIPS 2020 Stochastically Dominant Distributional Reinforcement Learning ICML 2020 Stochastic Approximate Gradient Descent via the Langevin Algorithm AAAI 2020 Stochastic bandits with arm-dependent delays ICML 2020 Stochastic Conditional Gradient Methods: From Convex Minimization to Submodular Maximization JMLR 2020 Stochastic Coordinate Minimization with Progressive Precision for Stochastic Convex Optimization ICML 2020 Stochastic Frank-Wolfe for Constrained Finite-Sum Minimization ICML 2020 Stochastic Gauss-Newton Algorithms for Nonconvex Compositional Optimization ICML 2020 Stochastic Gradient and Langevin Processes ICML 2020 Stochastic Hamiltonian Gradient Methods for Smooth Games ICML 2020 Stochasticity of Deterministic Gradient Descent: Large Learning Rate for Multiscale Objective Function NeurIPS 2020 Stochastic Online Learning with Probabilistic Graph Feedback AAAI 2020 Stochastic Optimization for Non-convex Inf-Projection Problems ICML 2020 Stochastic Optimization with Heavy-Tailed Noise via Accelerated Gradient Clipping NeurIPS 2020 Stochastic Optimization with Laggard Data Pipelines NeurIPS 2020 StochasticRank: Global Optimization of Scale-Free Discrete Functions ICML 2020 Stochastic Recursive Variance-Reduced Cubic Regularization Methods AISTATS 2020