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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)

Critical feature learning in deep neural networks ICML 2024 Critical Gap Between Generalization Error and Empirical Error in Active Learning WACV 2024 Critical Learning Periods Emerge Even in Deep Linear Networks ICLR 2024 Critical windows: non-asymptotic theory for feature emergence in diffusion models ICML 2024 CroMo-Mixup: Augmenting Cross-Model Representations for Continual Self-Supervised Learning ECCV 2024 CRONOS: Enhancing Deep Learning with Scalable GPU Accelerated Convex Neural Networks NeurIPS 2024 Cross-Linguistic Intelligibility of Non-Compositional Expressions in Spoken Context Interspeech 2024 CR-SAM: Curvature Regularized Sharpness-Aware Minimization AAAI 2024 CryoBench: Diverse and challenging datasets for the heterogeneity problem in cryo-EM NeurIPS 2024 CryoRL: Reinforcement Learning Enables Efficient Cryo-EM Data Collection WACV 2024 CryoSPIN: Improving Ab-Initio Cryo-EM Reconstruction with Semi-Amortized Pose Inference NeurIPS 2024 Cryptographic Hardness of Score Estimation NeurIPS 2024 Cumulative Regret Analysis of the Piyavskii–Shubert Algorithm and Its Variants for Global Optimization AAAI 2024 CURATRON: Complete and Robust Preference Data for Rigorous Alignment of Large Language Models NAACL 2024 Curriculum Learning for Small Code Language Models ACL 2024 Curvature Clues: Decoding Deep Learning Privacy with Input Loss Curvature NeurIPS 2024 Customized Subgraph Selection and Encoding for Drug-drug Interaction Prediction NeurIPS 2024 Cutting Off the Head Ends the Conflict: A Mechanism for Interpreting and Mitigating Knowledge Conflicts in Language Models ACL 2024 Cylindrical Thompson Sampling for High-Dimensional Bayesian Optimization AISTATS 2024 D^4: Dataset Distillation via Disentangled Diffusion Model CVPR 2024 DAdEE: Unsupervised Domain Adaptation in Early Exit PLMs EMNLP 2024 DAGER: Exact Gradient Inversion for Large Language Models NeurIPS 2024 DAG-Informed Structure Learning from Multi-Dimensional Point Processes JMLR 2024 DAGnosis: Localized Identification of Data Inconsistencies using Structures AISTATS 2024 DANCE: Dual-View Distribution Alignment for Dataset Condensation IJCAI 2024