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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)

Pointwise uncertainty quantification for sparse variational Gaussian process regression with a Brownian motion prior NeurIPS 2023 Poisson Process for Bayesian Optimization AutoML 2023 Polarity Is All You Need to Learn and Transfer Faster ICML 2023 Policy-Based Primal-Dual Methods for Convex Constrained Markov Decision Processes AAAI 2023 Policy Evaluation in Distributional LQR L4DC 2023 Policy Gradient for Rectangular Robust Markov Decision Processes NeurIPS 2023 Policy Gradient in Robust MDPs with Global Convergence Guarantee ICML 2023 Policy Optimization for Continuous Reinforcement Learning NeurIPS 2023 Polyhedral Complex Extraction from ReLU Networks using Edge Subdivision ICML 2023 Polynomially Over-Parameterized Convolutional Neural Networks Contain Structured Strong Winning Lottery Tickets NeurIPS 2023 Polynomial Preconditioning for Gradient Methods ICML 2023 Polynomial-Time Algorithms for Counting and Sampling Markov Equivalent DAGs with Applications JMLR 2023 Polynomial Time and Private Learning of Unbounded Gaussian Mixture Models ICML 2023 Polynomial-Time Linear-Swap Regret Minimization in Imperfect-Information Sequential Games NeurIPS 2023 Pose-Free Neural Radiance Fields via Implicit Pose Regularization ICCV 2023 Posterior Consistency for Bayesian Relevance Vector Machines JMLR 2023 Posterior Contraction for Deep Gaussian Process Priors JMLR 2023 Posterior Contraction Rates for Matérn Gaussian Processes on Riemannian Manifolds NeurIPS 2023 Posterior Coreset Construction with Kernelized Stein Discrepancy for Model-Based Reinforcement Learning AAAI 2023 Posterior sampling-based online learning for the stochastic shortest path model UAI 2023 Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation NeurIPS 2023 Posterior Tracking Algorithm for Classification Bandits AISTATS 2023 Post-Processing Temporal Action Detection CVPR 2023 POV-SLAM: Probabilistic Object-Aware Variational SLAM in Semi-Static Environments RSS 2023 Powerset multi-class cross entropy loss for neural speaker diarization Interspeech 2023