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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)

Sample-Efficient Iterative Lower Bound Optimization of Deep Reactive Policies for Planning in Continuous MDPs AAAI 2022 Sample-Efficient Reinforcement Learning in the Presence of Exogenous Information COLT 2022 Sample-Efficient Reinforcement Learning with loglog(T) Switching Cost ICML 2022 Sample Efficient Stochastic Policy Extragradient Algorithm for Zero-Sum Markov Game ICLR 2022 Sample Selection with Uncertainty of Losses for Learning with Noisy Labels ICLR 2022 Sample-Then-Optimize Batch Neural Thompson Sampling NeurIPS 2022 Sampling and Counting Acyclic Orientations in Chordal Graphs (Student Abstract) AAAI 2022 Sampling Approximately Low-Rank Ising Models: MCMC meets Variational Methods COLT 2022 Sampling-Based Approximations to Minimum Bayes Risk Decoding for Neural Machine Translation EMNLP 2022 Sampling-Based Robust Control of Autonomous Systems with Non-Gaussian Noise AAAI 2022 Sampling from Arbitrary Functions via PSD Models AISTATS 2022 Sampling from Log-Concave Distributions with Infinity-Distance Guarantees NeurIPS 2022 Sampling in Constrained Domains with Orthogonal-Space Variational Gradient Descent NeurIPS 2022 Sampling in Dirichlet Process Mixture Models for Clustering Streaming Data AISTATS 2022 Sampling Permutations for Shapley Value Estimation JMLR 2022 Sampling without Replacement Leads to Faster Rates in Finite-Sum Minimax Optimization NeurIPS 2022 Sampling with Riemannian Hamiltonian Monte Carlo in a Constrained Space NeurIPS 2022 Sandwich Batch Normalization: A Drop-In Replacement for Feature Distribution Heterogeneity WACV 2022 SAN: Stochastic Average Newton Algorithm for Minimizing Finite Sums AISTATS 2022 SAPD+: An Accelerated Stochastic Method for Nonconvex-Concave Minimax Problems NeurIPS 2022 SAPipe: Staleness-Aware Pipeline for Data Parallel DNN Training NeurIPS 2022 Saute RL: Almost Surely Safe Reinforcement Learning Using State Augmentation ICML 2022 Saving Stochastic Bandits from Poisoning Attacks via Limited Data Verification AAAI 2022 SC2-PCR: A Second Order Spatial Compatibility for Efficient and Robust Point Cloud Registration CVPR 2022 Scalable and Efficient Hypothesis Testing with Random Forests JMLR 2022