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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
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828
3,646
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2000
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Papers (including subtopics)

Federated Recommendation with Additive Personalization ICLR 2024 Federated Wasserstein Distance ICLR 2024 Federated X-armed Bandit AAAI 2024 FedFa: A Fully Asynchronous Training Paradigm for Federated Learning IJCAI 2024 FedFDD: Federated Learning with Frequency Domain Decomposition for Low-Dose CT Denoising MIDL 2024 FedFisher: Leveraging Fisher Information for One-Shot Federated Learning AISTATS 2024 FedGCS: A Generative Framework for Efficient Client Selection in Federated Learning via Gradient-based Optimization IJCAI 2024 FedGMark: Certifiably Robust Watermarking for Federated Graph Learning NeurIPS 2024 FedGTST: Boosting Global Transferability of Federated Models via Statistics Tuning NeurIPS 2024 FedHCA2: Towards Hetero-Client Federated Multi-Task Learning CVPR 2024 FedHyper: A Universal and Robust Learning Rate Scheduler for Federated Learning with Hypergradient Descent ICLR 2024 FedImpro: Measuring and Improving Client Update in Federated Learning ICLR 2024 FedLF: Layer-Wise Fair Federated Learning AAAI 2024 FedLMT: Tackling System Heterogeneity of Federated Learning via Low-Rank Model Training with Theoretical Guarantees ICML 2024 FedLPA: One-shot Federated Learning with Layer-Wise Posterior Aggregation NeurIPS 2024 FedMut: Generalized Federated Learning via Stochastic Mutation AAAI 2024 FedSC: Provable Federated Self-supervised Learning with Spectral Contrastive Objective over Non-i.i.d. Data ICML 2024 FedSOL: Stabilized Orthogonal Learning with Proximal Restrictions in Federated Learning CVPR 2024 FedTrans: Client-Transparent Utility Estimation for Robust Federated Learning ICLR 2024 Feedback-Based Adaptive Crossover-Rate in Evolutionary Computation IJCAI 2024 Feedback Efficient Online Fine-Tuning of Diffusion Models ICML 2024 Feed-Forward Latent Domain Adaptation WACV 2024 Feel-Good Thompson Sampling for Contextual Dueling Bandits ICML 2024 FERERO: A Flexible Framework for Preference-Guided Multi-Objective Learning NeurIPS 2024 FESSNC: Fast Exponentially Stable and Safe Neural Controller ICML 2024