3 citations · 12 across the 11 of their papers we have counts for
14 papers
Autoformulation of Mathematical Optimization Models Using LLMs
Nicolás Astorga, Tennison Liu, Yuanzhang Xiao +1
Mathematical optimization is fundamental to decision-making across diverse domains, from operations research to healthcare. Yet, translating real-world problems into optimization m…
Supply Function Equilibrium in Networked Electricity Markets
YuanzhangXiao, ChaithanyaBandi, Ermin Wei
We study deregulated power markets with strategic power suppliers. In deregulated markets, each supplier submits its supply function (i.e., the amount of electricity it is willing…
Unsupervised Massive MIMO Channel Estimation with Dual-Path Knowledge-Aware Auto-Encoders
Zhiheng Guo, Yuanzhang Xiao, Xiang Chen
In this paper, an unsupervised deep learning framework based on dual-path model-driven variational auto-encoders (VAE) is proposed for angle-of-arrivals (AoAs) and channel estimati…
PerFedRec++: Enhancing Personalized Federated Recommendation with Self-Supervised Pre-Training
Sichun Luo, Yuanzhang Xiao, Xinyi Zhang +3
Federated recommendation systems employ federated learning techniques to safeguard user privacy by transmitting model parameters instead of raw user data between user devices and t…
Adaptive Top-K in SGD for Communication-Efficient Distributed Learning
Mengzhe Ruan, Guangfeng Yan, Yuanzhang Xiao +2
Distributed stochastic gradient descent (SGD) with gradient compression has become a popular communication-efficient solution for accelerating distributed learning. One commonly us…
Towards Communication Efficient and Fair Federated Personalized Sequential Recommendation
Sichun Luo, Yuanzhang Xiao, Yang Liu +2
Federated recommendations leverage the federated learning (FL) techniques to make privacy-preserving recommendations. Though recent success in the federated recommender system, sev…