6 citations · 6 across the 4 of their papers we have counts for
6 papers
Learning to Optimize by Differentiable Programming
Liping Tao, Xindi Tong, Chee Wei Tan
Solving massive-scale optimization problems requires scalable first-order methods with low per-iteration cost. This tutorial highlights a shift in optimization: using differentiabl…
Adversarial Water-Filling: Theory, Algorithms and Foundation Model
Xindi Tong, Chee Wei Tan, H. Vincent Poor
Competitive resource allocation problems over frequency and space can be formulated as minimax interaction between transmit power and worst-case interference. This formulation natu…
Learning-Based Spectrum Cartography in Low Earth Orbit Satellite Networks: An Overview
Liping Tao, Xindi Tong, Chee Wei Tan
Low earth orbit (LEO) satellite networks are emerging as a key infrastructure for global connectivity and space-based sensing. Many tasks in such systems can be formulated as measu…
Certifying the Right to Be Forgotten: Primal-Dual Optimization for Sample and Label Unlearning in Vertical Federated Learning
Yu Jiang, Xindi Tong, Ziyao Liu +3
Federated unlearning has become an attractive approach to address privacy concerns in collaborative machine learning, for situations when sensitive data is remembered by AI models…
T3: A Novel Zero-shot Transfer Learning Framework Iteratively Training on an Assistant Task for a Target Task
Xindi Tong, Yujin Zhu, Shijian Fan +1
Long text summarization, gradually being essential for efficiently processing large volumes of information, stays challenging for Large Language Models (LLMs) such as GPT and LLaMA…
Efficient Federated Unlearning with Adaptive Differential Privacy Preservation
Yu Jiang, Xindi Tong, Ziyao Liu +3
Federated unlearning (FU) offers a promising solution to effectively address the need to erase the impact of specific clients' data on the global model in federated learning (FL),…