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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)

Metalearning Linear Bandits by Prior Update AISTATS 2022 Meta-Learning Priors for Safe Bayesian Optimization CoRL 2022 Meta-Learning with Fewer Tasks through Task Interpolation ICLR 2022 Meta-learning without data via Wasserstein distributionally-robust model fusion UAI 2022 MetaNODE: Prototype Optimization as a Neural ODE for Few-Shot Learning AAAI 2022 Meta Reinforcement Learning with Finite Training Tasks - a Density Estimation Approach NeurIPS 2022 Methods for Estimating and Improving Robustness of Language Models NAACL 2022 Metric Entropy Duality and the Sample Complexity of Outcome Indistinguishability ALT 2022 Metrics of Calibration for Probabilistic Predictions JMLR 2022 MidasTouch: Monte-Carlo inference over distributions across sliding touch CoRL 2022 Mildly Conservative Q-Learning for Offline Reinforcement Learning NeurIPS 2022 MIMO-DoAnet: Multi-channel Input and Multiple Outputs DoA Network with Unknown Number of Sound Sources Interspeech 2022 MINER: Improving Out-of-Vocabulary Named Entity Recognition from an Information Theoretic Perspective ACL 2022 Minibatch vs Local SGD with Shuffling: Tight Convergence Bounds and Beyond ICLR 2022 Minimal Expected Regret in Linear Quadratic Control AISTATS 2022 Minimax Classification under Concept Drift with Multidimensional Adaptation and Performance Guarantees ICML 2022 Minimax Kernel Machine Learning for a Class of Doubly Robust Functionals with Application to Proximal Causal Inference AISTATS 2022 Minimax M-estimation under Adversarial Contamination ICML 2022 Minimax Mixing Time of the Metropolis-Adjusted Langevin Algorithm for Log-Concave Sampling JMLR 2022 Minimax Optimal Algorithms for Fixed-Budget Best Arm Identification NeurIPS 2022 Minimax optimal approaches to the label shift problem in non-parametric settings JMLR 2022 Minimax Optimal Fixed-Budget Best Arm Identification in Linear Bandits NeurIPS 2022 Minimax Optimality (Probably) Doesn't Imply Distribution Learning for GANs ICLR 2022 Minimax Optimization with Smooth Algorithmic Adversaries ICLR 2022 Minimax Regret for Cascading Bandits NeurIPS 2022