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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)

Learning and Transferring Sparse Contextual Bigrams with Linear Transformers NeurIPS 2024 Learning a Single Neuron Robustly to Distributional Shifts and Adversarial Label Noise NeurIPS 2024 Learning a Spiking Neural Network for Efficient Image Deraining IJCAI 2024 Learning-Augmented Approximation Algorithms for Maximum Cut and Related Problems NeurIPS 2024 Learning-Augmented Dynamic Submodular Maximization NeurIPS 2024 Learning-Augmented Online Algorithm for Two-Level Ski-Rental Problem AAAI 2024 Learning-Based Algorithms for Graph Searching Problems AISTATS 2024 Learning-based rigid tube model predictive control L4DC 2024 Learning-Based Tracking-before-Detect for RF-Based Unconstrained Indoor Human Tracking IJCAI 2024 Learning Bayesian Network Classifiers to Minimize the Class Variable Parameters AAAI 2024 Learning bounded-degree polytrees with known skeleton ALT 2024 Learning Bregman Divergences with Application to Robustness NeurIPS 2024 Learning Cortico-Muscular Dependence through Orthonormal Decomposition of Density Ratios NeurIPS 2024 Learning Cut Generating Functions for Integer Programming NeurIPS 2024 Learning Decision Policies with Instrumental Variables through Double Machine Learning ICML 2024 Learning diffusion at lightspeed NeurIPS 2024 Learning Diffusion Priors from Observations by Expectation Maximization NeurIPS 2024 Learning Diffusions under Uncertainty AAAI 2024 Learning Discrete Concepts in Latent Hierarchical Models NeurIPS 2024 Learning Discrete-Time Major-Minor Mean Field Games AAAI 2024 Learning Discretized Neural Networks under Ricci Flow JMLR 2024 Learning Distributions on Manifolds with Free-Form Flows NeurIPS 2024 Learning-Efficient Yet Generalizable Collaborative Filtering for Item Recommendation ICML 2024 Learning Encodings for Constructive Neural Combinatorial Optimization Needs to Regret AAAI 2024 Learning Energy-Based Models by Cooperative Diffusion Recovery Likelihood ICLR 2024