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

Antigen-Specific Antibody Design via Direct Energy-based Preference Optimization NeurIPS 2024 AntLM: Bridging Causal and Masked Language Models CoNLL 2024 Anvil: Verifying Liveness of Cluster Management Controllers OSDI 2024 Any2Graph: Deep End-To-End Supervised Graph Prediction With An Optimal Transport Loss NeurIPS 2024 Any-dimensional equivariant neural networks AISTATS 2024 AnyFeature-VSLAM: Automating the Usage of Any Feature into Visual SLAM RSS 2024 Anytime-Constrained Reinforcement Learning AISTATS 2024 A PAC Learning Algorithm for LTL and Omega-Regular Objectives in MDPs AAAI 2024 A path-norm toolkit for modern networks: consequences, promises and challenges ICLR 2024 A PDE-based Explanation of Extreme Numerical Sensitivities and Edge of Stability in Training Neural Networks JMLR 2024 A Peek into Token Bias: Large Language Models Are Not Yet Genuine Reasoners EMNLP 2024 A Persuasive Approach to Combating Misinformation ICML 2024 A Physics-informed Low-rank Deep Neural Network for Blind and Universal Lens Aberration Correction CVPR 2024 A PID Controller Approach for Adaptive Probability-dependent Gradient Decay in Model Calibration NeurIPS 2024 API Is Enough: Conformal Prediction for Large Language Models Without Logit-Access EMNLP 2024 A Poincaré Inequality and Consistency Results for Signal Sampling on Large Graphs ICLR 2024 APOLLO: An Optimized Training Approach for Long-form Numerical Reasoning COLING 2024 A Polynomial Time, Pure Differentially Private Estimator for Binary Product Distributions ALT 2024 Apple Tasting: Combinatorial Dimensions and Minimax Rates COLT 2024 Application-Level Service Assurance with 5G RAN Slicing NSDI 2024 Applying Guidance in a Limited Interval Improves Sample and Distribution Quality in Diffusion Models NeurIPS 2024 Approximate Attributions for Off-the-Shelf Siamese Transformers EACL 2024 Approximate Bayesian Class-Conditional Models under Continuous Representation Shift AISTATS 2024 Approximate Bayesian inference from noisy likelihoods with Gaussian process emulated MCMC JMLR 2024 Approximated Orthogonal Projection Unit: Stabilizing Regression Network Training Using Natural Gradient NeurIPS 2024