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Optimization & Theory

43,292 papers (3 classified directly here)

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

Optimization (17,731) Learning Theory (6,809) Bayesian Inference (6,267) Theory (5,579) Statistical Learning (4,564) Neural Network Optimization (4,155) Stochastic Processes (2,948) Stochastic Methods (1,283) Loss Functions (1,220) Distributed Learning (1,202) Online Algorithms (1,013) Statistics (822) Generalization (376) Information Theory (370) Sample Complexity (282) Sparse Optimization (241) Game Theory (151) Convex Optimization (132) Optimal Transport (104) Robust Optimization (84) Distributed Optimization (73) Approximation Algorithms (33)

Papers per year

1
52
352
828
3,646
5,854
2000
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Papers (including subtopics)

Verifying vMVCC, a high-performance transaction library using multi-version concurrency control OSDI 2023 Very Fast, Approximate Counterfactual Explanations for Decision Forests AAAI 2023 VIBE: Topic-Driven Temporal Adaptation for Twitter Classification EMNLP 2023 Video Compression With Entropy-Constrained Neural Representations CVPR 2023 Video Probabilistic Diffusion Models in Projected Latent Space CVPR 2023 Vision Meets Definitions: Unsupervised Visual Word Sense Disambiguation Incorporating Gloss Information ACL 2023 VNE: An Effective Method for Improving Deep Representation by Manipulating Eigenvalue Distribution CVPR 2023 VOQL: Towards Optimal Regret in Model-free RL with Nonlinear Function Approximation COLT 2023 VOCE: Variational Optimization with Conservative Estimation for Offline Safe Reinforcement Learning NeurIPS 2023 Volume Feature Rendering for Fast Neural Radiance Field Reconstruction NeurIPS 2023 Volumetric Optimal Transportation by Fast Fourier Transform ICLR 2023 Vote’n’Rank: Revision of Benchmarking with Social Choice Theory EACL 2023 VRA: Variational Rectified Activation for Out-of-distribution Detection NeurIPS 2023 Wasserstein Barycenter Matching for Graph Size Generalization of Message Passing Neural Networks ICML 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 Gradient Flows for Optimizing Gaussian Mixture Policies NeurIPS 2023 Wasserstein Graph Distance Based on L1–Approximated Tree Edit Distance between Weisfeiler–Lehman Subtrees AAAI 2023 Wasserstein Quantum Monte Carlo: A Novel Approach for Solving the Quantum Many-Body Schrödinger Equation NeurIPS 2023 Weakly Coupled Deep Q-Networks NeurIPS 2023 Weakly Supervised Regression with Interval Targets ICML 2023 Weak Recovery Threshold for the Hypergraph Stochastic Block Model COLT 2023 We are Who We Cite: Bridges of Influence Between Natural Language Processing and Other Academic Fields EMNLP 2023 Weibull Racing Survival Analysis with Competing Events, Left Truncation, and Time-Varying Covariates JMLR 2023