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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)

Coordinate Descent Methods for Fractional Minimization ICML 2023 Coordinating Distributed Example Orders for Provably Accelerated Training NeurIPS 2023 CORE: Cooperative Training of Retriever-Reranker for Effective Dialogue Response Selection ACL 2023 Correcting discount-factor mismatch in on-policy policy gradient methods ICML 2023 Correction of Errors in Preference Ratings from Automated Metrics for Text Generation ACL 2023 Correlation Aware Sparsified Mean Estimation Using Random Projection NeurIPS 2023 Correlation Loss: Enforcing Correlation between Classification and Localization AAAI 2023 Corrupting Neuron Explanations of Deep Visual Features ICCV 2023 Corruption-Robust Algorithms with Uncertainty Weighting for Nonlinear Contextual Bandits and Markov Decision Processes ICML 2023 Corruption-Robust Offline Reinforcement Learning with General Function Approximation NeurIPS 2023 Corruption-Tolerant Algorithms for Generalized Linear Models AAAI 2023 Cosmic Microwave Background Recovery: A Graph-Based Bayesian Convolutional Network Approach AAAI 2023 Cost-effective Artificial Neural Networks IJCAI 2023 Cost-Effective Hyperparameter Optimization for Large Language Model Generation Inference AutoML 2023 Counterfactual Analysis in Dynamic Latent State Models ICML 2023 Counterfactual Conservative Q Learning for Offline Multi-agent Reinforcement Learning NeurIPS 2023 Counterfactual Evaluation of Peer-Review Assignment Policies NeurIPS 2023 Counterfactual Memorization in Neural Language Models NeurIPS 2023 Counterfactuals for the Future AAAI 2023 Couplformer: Rethinking Vision Transformer With Coupling Attention WACV 2023 Covariance-adaptive best arm identification NeurIPS 2023 Covariate balancing using the integral probability metric for causal inference ICML 2023 Covariate-Shift Generalization via Random Sample Weighting AAAI 2023 Coverage-centric Coreset Selection for High Pruning Rates ICLR 2023 CowClip: Reducing CTR Prediction Model Training Time from 12 Hours to 10 Minutes on 1 GPU AAAI 2023