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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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'25

Papers (including subtopics)

Delay-agnostic Asynchronous Coordinate Update Algorithm ICML 2023 Delayed Algorithms for Distributed Stochastic Weakly Convex Optimization NeurIPS 2023 Delayed Bandits: When Do Intermediate Observations Help? ICML 2023 Delayed Feedback in Generalised Linear Bandits Revisited AISTATS 2023 Delayed Feedback in Kernel Bandits ICML 2023 Delay-penalized CTC Implemented Based on Finite State Transducer Interspeech 2023 Deliberation and Voting in Approval-Based Multi-Winner Elections IJCAI 2023 DELS-MVS: Deep Epipolar Line Search for Multi-View Stereo WACV 2023 Delving into Evaluation Metrics for Generation: A Thorough Assessment of How Metrics Generalize to Rephrasing Across Languages AACL 2023 Delving into Semantic Scale Imbalance ICLR 2023 Delving into the Openness of CLIP ACL 2023 Demystifying Disagreement-on-the-Line in High Dimensions ICML 2023 Demystifying Oversmoothing in Attention-Based Graph Neural Networks NeurIPS 2023 Demystifying Softmax Gating Function in Gaussian Mixture of Experts NeurIPS 2023 Demystifying the Optimal Performance of Multi-Class Classification NeurIPS 2023 Demystify the Gravity Well in the Optimization Landscape (Student Abstract) AAAI 2023 Denoising Diffusion Samplers ICLR 2023 Denoising MCMC for Accelerating Diffusion-Based Generative Models ICML 2023 Dense-Exponential Random Features: Sharp Positive Estimators of the Gaussian Kernel NeurIPS 2023 Density Ratio Estimation and Neyman Pearson Classification with Missing Data AISTATS 2023 DepthFL : Depthwise Federated Learning for Heterogeneous Clients ICLR 2023 Depth Separation with Multilayer Mean-Field Networks ICLR 2023 Derandomized novelty detection with FDR control via conformal e-values NeurIPS 2023 Deriving Language Models from Masked Language Models ACL 2023 Design Amortization for Bayesian Optimal Experimental Design AAAI 2023