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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

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52
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828
3,646
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2000
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Papers (including subtopics)

Stochastic Attention Head Removal: A Simple and Effective Method for Improving Transformer Based ASR Models Interspeech 2021 Stochastic Bandits with Graph Feedback in Non-Stationary Environments AAAI 2021 Stochastic bandits with groups of similar arms. NeurIPS 2021 Stochastic Bandits with Linear Constraints AISTATS 2021 Stochastic Bias-Reduced Gradient Methods NeurIPS 2021 Stochastic continuous normalizing flows: training SDEs as ODEs UAI 2021 Stochastic Dueling Bandits with Adversarial Corruption ALT 2021 Stochastic Gradient Descent-Ascent and Consensus Optimization for Smooth Games: Convergence Analysis under Expected Co-coercivity NeurIPS 2021 Stochastic Gradient Descent Meets Distribution Regression AISTATS 2021 Stochastic Graphical Bandits with Adversarial Corruptions AAAI 2021 Stochastic Iterative Graph Matching ICML 2021 Stochastic Linear Bandits Robust to Adversarial Attacks AISTATS 2021 Stochastic model for sunk cost bias UAI 2021 Stochastic Multi-Armed Bandits with Control Variates NeurIPS 2021 Stochastic Multi-Armed Bandits with Unrestricted Delay Distributions ICML 2021 Stochastic Online Linear Regression: the Forward Algorithm to Replace Ridge NeurIPS 2021 Stochastic Online Optimization using Kalman Recursion JMLR 2021 Stochastic Optimization of Areas Under Precision-Recall Curves with Provable Convergence NeurIPS 2021 Stochastic optimization under time drift: iterate averaging, step-decay schedules, and high probability guarantees NeurIPS 2021 Stochastic Polyak Step-size for SGD: An Adaptive Learning Rate for Fast Convergence AISTATS 2021 Stochastic Process Regression for Cross-Cultural Speech Emotion Recognition Interspeech 2021 Stochastic Proximal AUC Maximization JMLR 2021 Stochastic Proximal Methods for Non-Smooth Non-Convex Constrained Sparse Optimization JMLR 2021 Stochastic Security: Adversarial Defense Using Long-Run Dynamics of Energy-Based Models ICLR 2021 Stochastic Shortest Path: Minimax, Parameter-Free and Towards Horizon-Free Regret NeurIPS 2021