11 papers
FedUP: One-Shot Federated Unlearning via Centroid-Guided Plug-in Filters
Feihong Nan, Zhengyi Zhong, Pan Wang +4
Federated unlearning (FU) is critical for complying with legal mandates like the right to be forgotten in decentralized systems, yet current methods face a persistent dilemma betwe…
Rethinking Efficiency in Neural Combinatorial Optimization: Batched Preference Optimization with Mamba
Zhenxing Xu, Zeyuan Ma, Weidong Bao +4
We study efficiency as a first-class objective in Neural Combinatorial Optimization (NCO) and present ECO, an efficient learning framework that combines batched preference optimiza…
AutoEP: LLMs-Driven Automation of Hyperparameter Evolution for Metaheuristic Algorithms
Zhenxing Xu, Yizhe Zhang, Weidong Bao +6
Dynamically configuring algorithm hyperparameters is a fundamental challenge in computational intelligence. While learning-based methods offer automation, they suffer from prohibit…
Fly0: Persistent Metric Anchoring for Zero-Shot Aerial Vision-Language Navigation
Zhenxing Xu, Brikit Lu, Yihong Lu +10
Current Visual-Language Navigation (VLN) methodologies face a trade-off between semantic understanding and control precision. While Multimodal Large Language Models (MLLMs) offer s…
Gains: Fine-grained Federated Domain Adaptation in Open Set
Zhengyi Zhong, Wenzheng Jiang, Weidong Bao +5
Conventional federated learning (FL) assumes a closed world with a fixed total number of clients. In contrast, new clients continuously join the FL process in real-world scenarios,…
SacFL: Self-Adaptive Federated Continual Learning for Resource-Constrained End Devices
Zhengyi Zhong, Weidong Bao, Ji Wang +3
The proliferation of end devices has led to a distributed computing paradigm, wherein on-device machine learning models continuously process diverse data generated by these devices…