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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)

Regarding Topology and Variant Frame Rates for Differentiable WFST-based End-to-End ASR Interspeech 2023 Regions of Reliability in the Evaluation of Multivariate Probabilistic Forecasts ICML 2023 Regression as Classification: Influence of Task Formulation on Neural Network Features AISTATS 2023 Regression-Free Model Updates for Spoken Language Understanding ACL 2023 Regression with Label Permutation in Generalized Linear Model ICML 2023 Regression with Sensor Data Containing Incomplete Observations ICML 2023 Regret Analysis of Online LQR Control via Trajectory Prediction and Tracking L4DC 2023 Regret Bounds for Markov Decision Processes with Recursive Optimized Certainty Equivalents ICML 2023 Regret Guarantees for Online Deep Control L4DC 2023 Regret Minimization and Convergence to Equilibria in General-sum Markov Games ICML 2023 Regret Minimization via Saddle Point Optimization NeurIPS 2023 Regret-Minimizing Double Oracle for Extensive-Form Games ICML 2023 Regret-Optimal Model-Free Reinforcement Learning for Discounted MDPs with Short Burn-In Time NeurIPS 2023 Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice ICML 2023 Regularization for Shuffled Data Problems via Exponential Family Priors on the Permutation Group AISTATS 2023 Regularization of Polynomial Networks for Image Recognition CVPR 2023 Regularize Implicit Neural Representation by Itself CVPR 2023 Regularizing Second-Order Influences for Continual Learning CVPR 2023 Regularizing Towards Soft Equivariance Under Mixed Symmetries ICML 2023 Rehearsal-Free Online Continual Learning for Automatic Speech Recognition Interspeech 2023 Rehearsal Learning for Avoiding Undesired Future NeurIPS 2023 ReHLine: Regularized Composite ReLU-ReHU Loss Minimization with Linear Computation and Linear Convergence NeurIPS 2023 Reinforced Approximate Exploratory Data Analysis AAAI 2023 Reinforced Sequence Training based Subjective Bias Correction EACL 2023 Reinforcement-Enhanced Autoregressive Feature Transformation: Gradient-steered Search in Continuous Space for Postfix Expressions NeurIPS 2023