Optimization

Fast Randomized Low-Rank Adaptation of Pre-trained Language Models with PAC Regularization ACL 2024 Fast Rates in Stochastic Online Convex Optimization by Exploiting the Curvature of Feasible Sets NeurIPS 2024 FastSAG: Towards Fast Non-Autoregressive Singing Accompaniment Generation IJCAI 2024 FastSurvival: Hidden Computational Blessings in Training Cox Proportional Hazards Models NeurIPS 2024 Fast TRAC: A Parameter-Free Optimizer for Lifelong Reinforcement Learning NeurIPS 2024 Fast two-time-scale stochastic gradient method with applications in reinforcement learning COLT 2024 Fast Updating Truncated SVD for Representation Learning with Sparse Matrices ICLR 2024 Feature-Adaptive and Data-Scalable In-Context Learning ACL 2024 Feature Distribution Matching by Optimal Transport for Effective and Robust Coreset Selection AAAI 2024 Feature Norm Regularized Federated Learning: Utilizing Data Disparities for Model Performance Gains IJCAI 2024 FedASMU: Efficient Asynchronous Federated Learning with Dynamic Staleness-Aware Model Update AAAI 2024 FedBPT: Efficient Federated Black-box Prompt Tuning for Large Language Models ICML 2024 FedCDA: Federated Learning with Cross-rounds Divergence-aware Aggregation ICLR 2024 FedCompass: Efficient Cross-Silo Federated Learning on Heterogeneous Client Devices Using a Computing Power-Aware Scheduler ICLR 2024 FedDA: Faster Adaptive Gradient Methods for Federated Constrained Optimization ICLR 2024 Federated Automatic Differentiation JMLR 2024 Federated Combinatorial Multi-Agent Multi-Armed Bandits ICML 2024 Federated Full-Parameter Tuning of Billion-Sized Language Models with Communication Cost under 18 Kilobytes ICML 2024 Federated Learning over Connected Modes NeurIPS 2024 Federated Learning under Periodic Client Participation and Heterogeneous Data: A New Communication-Efficient Algorithm and Analysis NeurIPS 2024 Federated Optimization with Doubly Regularized Drift Correction ICML 2024 Federated Orthogonal Training: Mitigating Global Catastrophic Forgetting in Continual Federated Learning ICLR 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 FedGCS: A Generative Framework for Efficient Client Selection in Federated Learning via Gradient-based Optimization IJCAI 2024