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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)

LSH-MoE: Communication-efficient MoE Training via Locality-Sensitive Hashing NeurIPS 2024 Lyapunov-Stable Deep Equilibrium Models AAAI 2024 Lyapunov-stable Neural Control for State and Output Feedback: A Novel Formulation ICML 2024 M2ASR: Multilingual Multi-task Automatic Speech Recognition via Multi-objective Optimization Interspeech 2024 M3C: A Framework towards Convergent, Flexible, and Unsupervised Learning of Mixture Graph Matching and Clustering ICLR 2024 M3D: Dataset Condensation by Minimizing Maximum Mean Discrepancy AAAI 2024 Machine Learning-Powered Combinatorial Clock Auction AAAI 2024 MacMic: Executing Iceberg Orders via Hierarchical Reinforcement Learning IJCAI 2024 MADA: Meta-Adaptive Optimizers Through Hyper-Gradient Descent ICML 2024 MadEye: Boosting Live Video Analytics Accuracy with Adaptive Camera Configurations NSDI 2024 Magnitude and timing of acceleration peaks in stressed and unstressed syllables Interspeech 2024 Magnitude Invariant Parametrizations Improve Hypernetwork Learning ICLR 2024 MAGNOLIA: Matching Algorithms via GNNs for Online Value-to-go Approximation ICML 2024 MagR: Weight Magnitude Reduction for Enhancing Post-Training Quantization NeurIPS 2024 Maintaining Diversity Provably Helps in Evolutionary Multimodal Optimization IJCAI 2024 Majority-of-Three: The Simplest Optimal Learner? COLT 2024 Make Continual Learning Stronger via C-Flat NeurIPS 2024 Make Large Language Model a Better Ranker EMNLP 2024 Make Me a BNN: A Simple Strategy for Estimating Bayesian Uncertainty from Pre-trained Models CVPR 2024 Make Prompt-based Black-Box Tuning Colorful: Boosting Model Generalization from Three Orthogonal Perspectives COLING 2024 MALIBO: Meta-learning for Likelihood-free Bayesian Optimization ICML 2024 MambaTree: Tree Topology is All You Need in State Space Model NeurIPS 2024 Manifold-Aligned Counterfactual Explanations for Neural Networks AISTATS 2024 Manifold Integrated Gradients: Riemannian Geometry for Feature Attribution ICML 2024 Manifold Learning by Mixture Models of VAEs for Inverse Problems JMLR 2024