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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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828
3,646
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2000
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Papers (including subtopics)

Improving sample efficiency of high dimensional Bayesian optimization with MCMC L4DC 2024 Improving SAM Requires Rethinking its Optimization Formulation ICML 2024 Improving Sharpness-Aware Minimization by Lookahead ICML 2024 Improving Socratic Question Generation using Data Augmentation and Preference Optimization NAACL 2024 Improving Speech-Based Dysarthria Detection using Multi-task Learning with Gradient Projection Interspeech 2024 Improving Statistical Significance in Human Evaluation of Automatic Metrics via Soft Pairwise Accuracy EMNLP 2024 Improving Subgroup Robustness via Data Selection NeurIPS 2024 Improving Temporal Link Prediction via Temporal Walk Matrix Projection NeurIPS 2024 Improving the Learning Capability of Small-size Image Restoration Network by Deep Fourier Shifting NeurIPS 2024 Improving the Training of Rectified Flows NeurIPS 2024 Improving the Worst-Case Bidirectional Communication Complexity for Nonconvex Distributed Optimization under Function Similarity NeurIPS 2024 Improving Training Efficiency of Diffusion Models via Multi-Stage Framework and Tailored Multi-Decoder Architecture CVPR 2024 Improving Transfer Learning by means of Ensemble Learning and Swarm Intelligence-based Neuroevolution AutoML 2024 In2Core: Leveraging Influence Functions for Coreset Selection in Instruction Finetuning of Large Language Models EMNLP 2024 Incentive-Aware Federated Learning with Training-Time Model Rewards ICLR 2024 Incentivizing Quality Text Generation via Statistical Contracts NeurIPS 2024 InceptionNeXt: When Inception Meets ConvNeXt CVPR 2024 IncomeSCM: From tabular data set to time-series simulator and causal estimation benchmark NeurIPS 2024 Inconsistency of Cross-Validation for Structure Learning in Gaussian Graphical Models AISTATS 2024 In-context Convergence of Transformers ICML 2024 In-Context Example Ordering Guided by Label Distributions NAACL 2024 In-Context Former: Lightning-fast Compressing Context for Large Language Model EMNLP 2024 In-Context Freeze-Thaw Bayesian Optimization for Hyperparameter Optimization ICML 2024 In-context Learning and Gradient Descent Revisited NAACL 2024 In-Context Learning Dynamics with Random Binary Sequences ICLR 2024