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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
352
828
3,646
5,854
2000
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Papers (including subtopics)

Communicating via Markov Decision Processes ICML 2022 Communication Acceleration of Local Gradient Methods via an Accelerated Primal-Dual Algorithm with an Inexact Prox NeurIPS 2022 Communication-Compressed Adaptive Gradient Method for Distributed Nonconvex Optimization AISTATS 2022 Communication-Constrained Distributed Quantile Regression with Optimal Statistical Guarantees JMLR 2022 Communication-Efficient Adaptive Federated Learning ICML 2022 Communication-efficient distributed eigenspace estimation with arbitrary node failures NeurIPS 2022 Communication Efficient Distributed Learning for Kernelized Contextual Bandits NeurIPS 2022 Communication-efficient Distributed Learning for Large Batch Optimization ICML 2022 Communication Efficient Federated Learning for Generalized Linear Bandits NeurIPS 2022 Communication-Efficient Topologies for Decentralized Learning with $O(1)$ Consensus Rate NeurIPS 2022 Comparing Distributional and Curated Approaches for Cross-lingual Frame Alignment NAACL 2022 Comparing Distributions by Measuring Differences that Affect Decision Making ICLR 2022 Complete Policy Regret Bounds for Tallying Bandits COLT 2022 Complete Verification via Multi-Neuron Relaxation Guided Branch-and-Bound ICLR 2022 Complex Hyperbolic Knowledge Graph Embeddings with Fast Fourier Transform EMNLP 2022 Complexity of Deliberative Coalition Formation AAAI 2022 Complex Momentum for Optimization in Games AISTATS 2022 Composable Sparse Fine-Tuning for Cross-Lingual Transfer ACL 2022 Compositional Training for End-to-End Deep AUC Maximization ICLR 2022 Composition Theorems for Interactive Differential Privacy NeurIPS 2022 Comprehensive Analysis of Negative Sampling in Knowledge Graph Representation Learning ICML 2022 Compressed-VFL: Communication-Efficient Learning with Vertically Partitioned Data ICML 2022 Computationally Efficient Horizon-Free Reinforcement Learning for Linear Mixture MDPs NeurIPS 2022 Computationally Efficient Optimization of Plackett-Luce Ranking Models for Relevance and Fairness (Extended Abstract) IJCAI 2022 Computational-Statistical Gap in Reinforcement Learning COLT 2022