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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)

PAC Learning of Halfspaces with Malicious Noise in Nearly Linear Time AISTATS 2023 PAC-NeRF: Physics Augmented Continuum Neural Radiance Fields for Geometry-Agnostic System Identification ICLR 2023 PAC Prediction Sets for Large Language Models of Code ICML 2023 PAC Reinforcement Learning for Predictive State Representations ICLR 2023 PAC-tuning: Fine-tuning Pre-trained Language Models with PAC-driven Perturbed Gradient Descent EMNLP 2023 PAC Verification of Statistical Algorithms COLT 2023 PA&DA: Jointly Sampling Path and Data for Consistent NAS CVPR 2023 PAI at SemEval-2023 Task 4: A General Multi-label Classification System with Class-balanced Loss Function and Ensemble Module SemEval 2023 Parallel Q-Learning: Scaling Off-policy Reinforcement Learning under Massively Parallel Simulation ICML 2023 Parallel Deep Neural Networks Have Zero Duality Gap ICLR 2023 Parallel-mentoring for Offline Model-based Optimization NeurIPS 2023 Parameter-Efficient Model Adaptation for Vision Transformers AAAI 2023 Parameter-efficient Tuning for Large Language Model without Calculating Its Gradients EMNLP 2023 Parameter-Level Soft-Masking for Continual Learning ICML 2023 Parametric Information Maximization for Generalized Category Discovery ICCV 2023 Parametric Surface Constrained Upsampler Network for Point Cloud AAAI 2023 Parametrized Gradual Semantics Dealing with Varied Degrees of Compensation IJCAI 2023 Pareto Frontiers in Deep Feature Learning: Data, Compute, Width, and Luck NeurIPS 2023 Pareto Manifold Learning: Tackling multiple tasks via ensembles of single-task models ICML 2023 Pareto Regret Analyses in Multi-objective Multi-armed Bandit ICML 2023 Partial Counterfactual Identification of Continuous Outcomes with a Curvature Sensitivity Model NeurIPS 2023 Partial-Label Regression AAAI 2023 Partially Calibrated Semi-Generalized Pose From Hybrid Point Correspondences WACV 2023 Partially Observable RL with B-Stability: Unified Structural Condition and Sharp Sample-Efficient Algorithms ICLR 2023 Partial Order in Chaos: Consensus on Feature Attributions in the Rashomon Set JMLR 2023