Optimization

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 FedLF: Layer-Wise Fair Federated Learning AAAI 2024 FedMut: Generalized Federated Learning via Stochastic Mutation AAAI 2024 FedSOL: Stabilized Orthogonal Learning with Proximal Restrictions in Federated Learning CVPR 2024 Feedback Efficient Online Fine-Tuning of Diffusion Models ICML 2024 Feed-Forward Latent Domain Adaptation WACV 2024 FERERO: A Flexible Framework for Preference-Guided Multi-Objective Learning NeurIPS 2024 Fewer Truncations Improve Language Modeling ICML 2024 Few-Shot Diffusion Models Escape the Curse of Dimensionality NeurIPS 2024 FFN-SkipLLM: A Hidden Gem for Autoregressive Decoding with Adaptive Feed Forward Skipping EMNLP 2024 FFSTC: Fongbe to French Speech Translation Corpus COLING 2024 Fiber Monte Carlo ICLR 2024 Fill In The Gaps: Model Calibration and Generalization with Synthetic Data EMNLP 2024 Filtered Direct Preference Optimization EMNLP 2024 FilterNet: Harnessing Frequency Filters for Time Series Forecasting NeurIPS 2024 Finding Adversarial Inputs for Heuristics using Multi-level Optimization NSDI 2024 Finding good policies in average-reward Markov Decision Processes without prior knowledge NeurIPS 2024 Fine-grained Analysis of In-context Linear Estimation: Data, Architecture, and Beyond NeurIPS 2024 Fine-grained Analysis of Stability and Generalization for Stochastic Bilevel Optimization IJCAI 2024 Fine-Grained Dynamic Framework for Bias-Variance Joint Optimization on Data Missing Not at Random NeurIPS 2024 Fine-grained Pluggable Gradient Ascent for Knowledge Unlearning in Language Models EMNLP 2024 Fine-Tuning and Prompt Optimization: Two Great Steps that Work Better Together EMNLP 2024 Finite-State Autoregressive Entropy Coding for Efficient Learned Lossless Compression ICLR 2024