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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)

CHSEL: Producing Diverse Plausible Pose Estimates from Contact and Free Space Data RSS 2023 CICL_DMS at SemEval-2023 Task 11: Learning With Disagreements (Le-Wi-Di) SemEval 2023 CircuitNet: A Generic Neural Network to Realize Universal Circuit Motif Modeling ICML 2023 Class Adaptive Network Calibration CVPR 2023 Class based Influence Functions for Error Detection ACL 2023 Class-Conditional Sharpness-Aware Minimization for Deep Long-Tailed Recognition CVPR 2023 Classically Approximating Variational Quantum Machine Learning with Random Fourier Features ICLR 2023 Classical Out-of-Distribution Detection Methods Benchmark in Text Classification Tasks ACL 2023 Classification of Heavy-tailed Features in High Dimensions: a Superstatistical Approach NeurIPS 2023 Client-Customized Adaptation for Parameter-Efficient Federated Learning ACL 2023 CLIP-OGD: An Experimental Design for Adaptive Neyman Allocation in Sequential Experiments NeurIPS 2023 Closer Look at the Transferability of Adversarial Examples: How They Fool Different Models Differently WACV 2023 Closing the gap between the upper bound and lower bound of Adam's iteration complexity NeurIPS 2023 Clustered Federated Learning for Heterogeneous Data (Student Abstract) AAAI 2023 Cluster Explanation via Polyhedral Descriptions ICML 2023 Clusterformer: Cluster-based Transformer for 3D Object Detection in Point Clouds ICCV 2023 Clustering above Exponential Families with Tempered Exponential Measures AISTATS 2023 Clustering What Matters: Optimal Approximation for Clustering with Outliers AAAI 2023 CMA-ES for Post Hoc Ensembling in AutoML: A Great Success and Salvageable Failure AutoML 2023 Coarse-Grained Smoothness for Reinforcement Learning in Metric Spaces AISTATS 2023 Coarse-to-Fine: a Hierarchical Diffusion Model for Molecule Generation in 3D ICML 2023 CO-BED: Information-Theoretic Contextual Optimization via Bayesian Experimental Design ICML 2023 CocktailSGD: Fine-tuning Foundation Models over 500Mbps Networks ICML 2023 Coco at SemEval-2023 Task 10: Explainable Detection of Online Sexism SemEval 2023 CodaLab Competitions: An Open Source Platform to Organize Scientific Challenges JMLR 2023