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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)

A Fast Algorithm for PAC Combinatorial Pure Exploration AAAI 2022 A fast and accurate splitting method for optimal transport: analysis and implementation ICLR 2022 A Fast Post-Training Pruning Framework for Transformers NeurIPS 2022 A Fast Scale-Invariant Algorithm for Non-negative Least Squares with Non-negative Data NeurIPS 2022 A Few Expert Queries Suffices for Sample-Efficient RL with Resets and Linear Value Approximation NeurIPS 2022 A Few More Examples May Be Worth Billions of Parameters EMNLP 2022 Affective Idiosyncratic Responses to Music EMNLP 2022 A Flexible Meta Learning Model for Image Registration MIDL 2022 A Fourier Approach to Mixture Learning NeurIPS 2022 AFRNN: Stable RNN with Top Down Feedback and Antisymmetry ACML 2022 A Fully Single Loop Algorithm for Bilevel Optimization without Hessian Inverse AAAI 2022 A Functional Information Perspective on Model Interpretation ICML 2022 A General Analysis of Example-Selection for Stochastic Gradient Descent ICLR 2022 A general approximation lower bound in L^p norm, with applications to feed-forward neural networks NeurIPS 2022 A general class of surrogate functions for stable and efficient reinforcement learning AISTATS 2022 A General Framework for Auditing Differentially Private Machine Learning NeurIPS 2022 A Generalized Bootstrap Target for Value-Learning, Efficiently Combining Value and Feature Predictions AAAI 2022 A Generalized Weighted Optimization Method for Computational Learning and Inversion ICLR 2022 A General Recipe for Likelihood-free Bayesian Optimization ICML 2022 A general sample complexity analysis of vanilla policy gradient AISTATS 2022 A Gentle Introduction to Deep Nets and Opportunities for the Future ACL 2022 A geometric method for improved uncertainty estimation in real-time UAI 2022 A global analysis of metrics used for measuring performance in natural language processing ACL 2022 A global convergence theory for deep ReLU implicit networks via over-parameterization ICLR 2022 A Globally Convergent Evolutionary Strategy for Stochastic Constrained Optimization with Applications to Reinforcement Learning AISTATS 2022