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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)

HD-Eval: Aligning Large Language Model Evaluators Through Hierarchical Criteria Decomposition ACL 2024 Head-to-Tail: How Knowledgeable are Large Language Models (LLMs)? A.K.A. Will LLMs Replace Knowledge Graphs? NAACL 2024 Heavy-Tailed Class Imbalance and Why Adam Outperforms Gradient Descent on Language Models NeurIPS 2024 HEMM: Holistic Evaluation of Multimodal Foundation Models NeurIPS 2024 HEPrune: Fast Private Training of Deep Neural Networks With Encrypted Data Pruning NeurIPS 2024 Here’s a Free Lunch: Sanitizing Backdoored Models with Model Merge ACL 2024 Heterogeneity-aware Clustered Distributed Learning for Multi-source Data Analysis JMLR 2024 Heterogeneity-Guided Client Sampling: Towards Fast and Efficient Non-IID Federated Learning NeurIPS 2024 Heterogeneous Personalized Federated Learning by Local-Global Updates Mixing via Convergence Rate ICLR 2024 HGCN2SP: Hierarchical Graph Convolutional Network for Two-Stage Stochastic Programming ICML 2024 HGP-NLP at BioLaySumm: Leveraging LoRA for Lay Summarization of Biomedical Research Articles using Seq2Seq Transformers ACL 2024 HHD-GP: Incorporating Helmholtz-Hodge Decomposition into Gaussian Processes for Learning Dynamical Systems NeurIPS 2024 Hidden Persuaders: LLMs’ Political Leaning and Their Influence on Voters EMNLP 2024 Hidden Traveling Waves bind Working Memory Variables in Recurrent Neural Networks ICML 2024 Hidden yet quantifiable: A lower bound for confounding strength using randomized trials AISTATS 2024 Hierarchical and Density-based Causal Clustering NeurIPS 2024 Hierarchical Federated Learning with Multi-Timescale Gradient Correction NeurIPS 2024 Hierarchical Global Asynchronous Federated Learning Across Multi-Center ACML 2024 Hierarchical Hybrid Sliced Wasserstein: A Scalable Metric for Heterogeneous Joint Distributions NeurIPS 2024 Hierarchical Selection of Important Context for Generative Event Causality Identification with Optimal Transports COLING 2024 Hierarchical Uncertainty Exploration via Feedforward Posterior Trees NeurIPS 2024 Hierarchize Pareto Dominance in Multi-Objective Stochastic Linear Bandits AAAI 2024 HiFT: A Hierarchical Full Parameter Fine-Tuning Strategy EMNLP 2024 High-Dimensional Analysis for Generalized Nonlinear Regression: From Asymptotics to Algorithm AAAI 2024 High-Dimensional Bayesian Optimization via Semi-Supervised Learning with Optimized Unlabeled Data Sampling ICML 2024