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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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'25

Papers (including subtopics)

Learning-Enabled Robust Control with Noisy Measurements L4DC 2022 Learning Energy Networks with Generalized Fenchel-Young Losses NeurIPS 2022 Learning Expected Emphatic Traces for Deep RL AAAI 2022 Learning Fast Samplers for Diffusion Models by Differentiating Through Sample Quality ICLR 2022 Learning First-Order Rules with Differentiable Logic Program Semantics IJCAI 2022 Learning Forward Dynamics Model and Informed Trajectory Sampler for Safe Quadruped Navigation RSS 2022 Learning Fractional White Noises in Neural Stochastic Differential Equations NeurIPS 2022 Learning from an Exploring Demonstrator: Optimal Reward Estimation for Bandits AISTATS 2022 Learning from Few Samples: Transformation-Invariant SVMs with Composition and Locality at Multiple Scales NeurIPS 2022 Learning from Label Proportions by Learning with Label Noise NeurIPS 2022 Learning from Mistakes – a Framework for Neural Architecture Search AAAI 2022 Learning from Stochastically Revealed Preference NeurIPS 2022 Learning General Halfspaces with Adversarial Label Noise via Online Gradient Descent ICML 2022 Learning GMMs with Nearly Optimal Robustness Guarantees COLT 2022 Learning Graph Regularisation for Guided Super-Resolution CVPR 2022 LEARNING GUARANTEES FOR GRAPH CONVOLUTIONAL NETWORKS ON THE STOCHASTIC BLOCK MODEL ICLR 2022 Learning Higher-Order Logic Programs From Failures IJCAI 2022 Learning Infinite-horizon Average-reward Markov Decision Process with Constraints ICML 2022 Learning Infinite-Horizon Average-Reward Restless Multi-Action Bandits via Index Awareness NeurIPS 2022 Learning Influence Adoption in Heterogeneous Networks AAAI 2022 Learning in Observable POMDPs, without Computationally Intractable Oracles NeurIPS 2022 Learning Interface Conditions in Domain Decomposition Solvers NeurIPS 2022 Learning Interpretable BEV Based VIO without Deep Neural Networks CoRL 2022 Learning invariant weights in neural networks UAI 2022 Learning Iterative Reasoning through Energy Minimization ICML 2022