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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

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52
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828
3,646
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2000
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Papers (including subtopics)

Self-Compatibility: Evaluating Causal Discovery without Ground Truth AISTATS 2024 Self-Consistency Training for Density-Functional-Theory Hamiltonian Prediction ICML 2024 Self-Consuming Generative Models Go MAD ICLR 2024 Self-Consuming Generative Models with Curated Data Provably Optimize Human Preferences NeurIPS 2024 Self-Distillation Regularized Connectionist Temporal Classification Loss for Text Recognition: A Simple Yet Effective Approach AAAI 2024 Self-Evolution Fine-Tuning for Policy Optimization EMNLP 2024 Self-Modifying State Modeling for Simultaneous Machine Translation ACL 2024 Self-Recognition in Language Models EMNLP 2024 Self-Refining Diffusion Samplers: Enabling Parallelization via Parareal Iterations NeurIPS 2024 Self-Renewal Prompt Optimizing with Implicit Reasoning EMNLP 2024 Self-Repellent Random Walks on General Graphs - Achieving Minimal Sampling Variance via Nonlinear Markov Chains (Extended Abstract) IJCAI 2024 Self-Rewarding Language Models ICML 2024 Self-Supervised 3D Human Mesh Recovery from a Single Image with Uncertainty-Aware Learning AAAI 2024 Self-supervised Debiasing Using Low Rank Regularization CVPR 2024 Self-Supervised Denoising Transformer With Gaussian Process WACV 2024 Self-training Language Models for Arithmetic Reasoning EMNLP 2024 Semantic-Aware Multi-Label Adversarial Attacks CVPR 2024 Semantic Density: Uncertainty Quantification for Large Language Models through Confidence Measurement in Semantic Space NeurIPS 2024 Semidefinite Relaxations of the Gromov-Wasserstein Distance NeurIPS 2024 Semiparametric Efficient Inference in Adaptive Experiments CLeaR 2024 Semi-Random Matrix Completion via Flow-Based Adaptive Reweighting NeurIPS 2024 Semi-supervised Inference for Block-wise Missing Data without Imputation JMLR 2024 Semi-Supervised Sparse Gaussian Classification: Provable Benefits of Unlabeled Data NeurIPS 2024 Semi-Truths: A Large-Scale Dataset of AI-Augmented Images for Evaluating Robustness of AI-Generated Image detectors NeurIPS 2024 SENIT at AraFinNLP2024: trust your model or combine two ACL 2024