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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)

Model Collapse Demystified: The Case of Regression NeurIPS 2024 Model Editing Harms General Abilities of Large Language Models: Regularization to the Rescue EMNLP 2024 Model-free Low-Rank Reinforcement Learning via Leveraged Entry-wise Matrix Estimation NeurIPS 2024 Model-Free Robust $φ$-Divergence Reinforcement Learning Using Both Offline and Online Data ICML 2024 Model-Free Robust Reinforcement Learning with Sample Complexity Analysis UAI 2024 Model Fusion through Bayesian Optimization in Language Model Fine-Tuning NeurIPS 2024 Modeling Latent Neural Dynamics with Gaussian Process Switching Linear Dynamical Systems NeurIPS 2024 Modeling probabilistic reduction across domains with Naive Discriminative Learning Interspeech 2024 Modeling Random Networks with Heterogeneous Reciprocity JMLR 2024 Modeling state-dependent communication between brain regions with switching nonlinear dynamical systems ICLR 2024 Model Merging by Uncertainty-Based Gradient Matching ICLR 2024 Model Reconstruction Using Counterfactual Explanations: A Perspective From Polytope Theory NeurIPS 2024 MoE-I2: Compressing Mixture of Experts Models through Inter-Expert Pruning and Intra-Expert Low-Rank Decomposition EMNLP 2024 MogaNet: Multi-order Gated Aggregation Network ICLR 2024 Molecular Optimization Model with Patentability Constraint AAAI 2024 Mollification Effects of Policy Gradient Methods ICML 2024 Momentum Benefits Non-iid Federated Learning Simply and Provably ICLR 2024 Momentum for the Win: Collaborative Federated Reinforcement Learning across Heterogeneous Environments ICML 2024 Momentum Particle Maximum Likelihood ICML 2024 MoMo: Momentum Models for Adaptive Learning Rates ICML 2024 Monitoring machine learning-based risk prediction algorithms in the presence of performativity AISTATS 2024 Monomial Matrix Group Equivariant Neural Functional Networks NeurIPS 2024 Monotone, Bi-Lipschitz, and Polyak-Łojasiewicz Networks ICML 2024 Monotone Individual Fairness ICML 2024 Monotonic Paraphrasing Improves Generalization of Language Model Prompting EMNLP 2024