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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)

MurTree: Optimal Decision Trees via Dynamic Programming and Search JMLR 2022 Mutual Information Alleviates Hallucinations in Abstractive Summarization EMNLP 2022 Mutual Information Constraints for Monte-Carlo Objectives to Prevent Posterior Collapse Especially in Language Modelling JMLR 2022 NAS-Bench-360: Benchmarking Neural Architecture Search on Diverse Tasks NeurIPS 2022 NAS-Bench-Graph: Benchmarking Graph Neural Architecture Search NeurIPS 2022 NAS-Bench-Suite: NAS Evaluation is (Now) Surprisingly Easy ICLR 2022 NAS-Bench-Suite-Zero: Accelerating Research on Zero Cost Proxies NeurIPS 2022 NASI: Label- and Data-agnostic Neural Architecture Search at Initialization ICLR 2022 NASPY: Automated Extraction of Automated Machine Learning Models ICLR 2022 NAS-VAD: Neural Architecture Search for Voice Activity Detection Interspeech 2022 Natural gradient enables fast sampling in spiking neural networks NeurIPS 2022 Natural image synthesis for the retina with variational information bottleneck representation NeurIPS 2022 NaturalInversion: Data-Free Image Synthesis Improving Real-World Consistency AAAI 2022 Near-Exact Recovery for Tomographic Inverse Problems via Deep Learning ICML 2022 Near Instance Optimal Model Selection for Pure Exploration Linear Bandits AISTATS 2022 Near Instance-Optimal PAC Reinforcement Learning for Deterministic MDPs NeurIPS 2022 Nearly Minimax Optimal Regret for Learning Infinite-horizon Average-reward MDPs with Linear Function Approximation AISTATS 2022 Nearly Minimax Optimal Reinforcement Learning with Linear Function Approximation ICML 2022 Nearly Optimal Algorithms for Level Set Estimation AISTATS 2022 Nearly Optimal Algorithms for Linear Contextual Bandits with Adversarial Corruptions NeurIPS 2022 Nearly Optimal Best-of-Both-Worlds Algorithms for Online Learning with Feedback Graphs NeurIPS 2022 Nearly Optimal Catoni’s M-estimator for Infinite Variance ICML 2022 Nearly Optimal Policy Optimization with Stable at Any Time Guarantee ICML 2022 (Nearly) Optimal Private Linear Regression for Sub-Gaussian Data via Adaptive Clipping COLT 2022 Nearly-Tight Bounds for Testing Histogram Distributions NeurIPS 2022