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)

Variance-Dependent Regret Bounds for Linear Bandits and Reinforcement Learning: Adaptivity and Computational Efficiency COLT 2023 Variance-Reduced Gradient Estimation via Noise-Reuse in Online Evolution Strategies NeurIPS 2023 Variance Reduced Online Gradient Descent for Kernelized Pairwise Learning with Limited Memory ACML 2023 Variational Annealing on Graphs for Combinatorial Optimization NeurIPS 2023 Variational Inference with Gaussian Score Matching NeurIPS 2023 Variational Wasserstein Barycenters with C-cyclical Monotonicity Regularization AAAI 2023 Variational Weighting for Kernel Density Ratios NeurIPS 2023 VCG Mechanism Design with Unknown Agent Values under Stochastic Bandit Feedback JMLR 2023 Vector Optimization with Stochastic Bandit Feedback AISTATS 2023 VISinger2: High-Fidelity End-to-End Singing Voice Synthesis Enhanced by Digital Signal Processing Synthesizer Interspeech 2023 Vote’n’Rank: Revision of Benchmarking with Social Choice Theory EACL 2023 Voting with Preference Intensities AAAI 2023 Walkability Optimization: Formulations, Algorithms, and a Case Study of Toronto AAAI 2023 Warm-Starting Nested Rollout Policy Adaptation with Optimal Stopping AAAI 2023 Wasserstein Distributional Learning via Majorization-Minimization AISTATS 2023 Wasserstein Distributionally Robust Linear-Quadratic Estimation under Martingale Constraints AISTATS 2023 Wasserstein distributional robustness of neural networks NeurIPS 2023 Wasserstein-Fisher-Rao Embedding: Logical Query Embeddings with Local Comparison and Global Transport ACL 2023 Wasserstein Gradient Flows for Optimizing Gaussian Mixture Policies NeurIPS 2023 Weighted Tallying Bandits: Overcoming Intractability via Repeated Exposure Optimality ICML 2023 Weitzman's Rule for Pandora's Box with Correlations NeurIPS 2023 When can Regression-Adjusted Control Variate Help? Rare Events, Sobolev Embedding and Minimax Optimality NeurIPS 2023 When Gradient Descent Meets Derivative-Free Optimization: A Match Made in Black-Box Scenario ACL 2023 When Online Learning Meets ODE: Learning without Forgetting on Variable Feature Space AAAI 2023 “Why Not Looking backward?” A Robust Two-Step Method to Automatically Terminate Bayesian Optimization NeurIPS 2023