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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)

MiLe Loss: a New Loss for Mitigating the Bias of Learning Difficulties in Generative Language Models NAACL 2024 MiLoRA: Efficient Mixture of Low-Rank Adaptation for Large Language Models Fine-tuning EMNLP 2024 MILP-FBGen: LP/MILP Instance Generation with Feasibility/Boundedness ICML 2024 MIM-Reasoner: Learning with Theoretical Guarantees for Multiplex Influence Maximization AISTATS 2024 MINDE: Mutual Information Neural Diffusion Estimation ICLR 2024 Mind the Gap: A Causal Perspective on Bias Amplification in Prediction & Decision-Making NeurIPS 2024 Mind the GAP: Improving Robustness to Subpopulation Shifts with Group-Aware Priors AISTATS 2024 Minibatch Stochastic Three Points Method for Unconstrained Smooth Minimization AAAI 2024 Minimal Perspective Autocalibration CVPR 2024 Minimax Excess Risk of First-Order Methods for Statistical Learning with Data-Dependent Oracles AISTATS 2024 Minimax Linear Regression under the Quantile Risk COLT 2024 Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning NeurIPS 2024 Minimax optimal density estimation using a shallow generative model with a one-dimensional latent variable AISTATS 2024 Minimax optimality of convolutional neural networks for infinite dimensional input-output problems and separation from kernel methods ICLR 2024 Minimax Optimality of Score-based Diffusion Models: Beyond the Density Lower Bound Assumptions ICML 2024 Minimax-optimal reward-agnostic exploration in reinforcement learning COLT 2024 Minimax Rates for High-Dimensional Random Tessellation Forests JMLR 2024 Minimax Risk Classifiers for Mislabeled Data: a Study on Patient Outcome Prediction Tasks MLHC 2024 Minimizing f-Divergences by Interpolating Velocity Fields ICML 2024 Minimizing Convex Functionals over Space of Probability Measures via KL Divergence Gradient Flow AISTATS 2024 Minimizing Layerwise Activation Norm Improves Generalization in Federated Learning WACV 2024 Minimizing UCB: a Better Local Search Strategy in Local Bayesian Optimization NeurIPS 2024 Minimum Coverage Sets for Training Robust Ad Hoc Teamwork Agents AAAI 2024 Minimum Entropy Coupling with Bottleneck NeurIPS 2024 Minimum Norm Interpolation Meets The Local Theory of Banach Spaces ICML 2024