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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)

Learning Thresholds with Latent Values and Censored Feedback ICLR 2024 Learning to Approximate Adaptive Kernel Convolution on Graphs AAAI 2024 Learning to be Smooth: An End-to-End Differentiable Particle Smoother NeurIPS 2024 Learning to Build Solutions in Stochastic Matching Problems Using Flows (Student Abstract) AAAI 2024 Learning to compute Gröbner bases NeurIPS 2024 Learning to Continually Learn with the Bayesian Principle ICML 2024 Learning to Embed Distributions via Maximum Kernel Entropy NeurIPS 2024 Learning to Explore for Stochastic Gradient MCMC ICML 2024 Learning to Make Keypoints Sub-Pixel Accurate ECCV 2024 Learning to Maximize Mutual Information for Chain-of-Thought Distillation ACL 2024 Learning to Pivot as a Smart Expert AAAI 2024 Learning to Predict Structural Vibrations NeurIPS 2024 Learning to Price Homogeneous Data NeurIPS 2024 Learning to Reason via Program Generation, Emulation, and Search NeurIPS 2024 Learning to Remove Cuts in Integer Linear Programming ICML 2024 Learning to Reweight for Generalizable Graph Neural Network AAAI 2024 Learning to Scale Logits for Temperature-Conditional GFlowNets ICML 2024 Learning to Shape In-distribution Feature Space for Out-of-distribution Detection NeurIPS 2024 Learning to Solve Bilevel Programs with Binary Tender ICLR 2024 Learning to Solve Quadratic Unconstrained Binary Optimization in a Classification Way NeurIPS 2024 Learning to Solve the Constrained Most Probable Explanation Task in Probabilistic Graphical Models AISTATS 2024 Learning to Stop Cut Generation for Efficient Mixed-Integer Linear Programming AAAI 2024 Learning to Understand: Identifying Interactions via the Möbius Transform NeurIPS 2024 Learning to Warm-Start Fixed-Point Optimization Algorithms JMLR 2024 Learning to Write Rationally: How Information Is Distributed in Non-native Speakers’ Essays EMNLP 2024