78 citations · 151 across the 6 of their papers we have counts for
6 papers
Federated PAC-Bayesian Learning on Non-IID data
Zihao Zhao, Yang Liu, Wenbo Ding +1
Existing research has either adapted the Probably Approximately Correct (PAC) Bayesian framework for federated learning (FL) or used information-theoretic PAC-Bayesian bounds while…
AQUILA: Communication Efficient Federated Learning with Adaptive Quantization in Device Selection Strategy
Zihao Zhao, Yuzhu Mao, Zhenpeng Shi +4
The widespread adoption of Federated Learning (FL), a privacy-preserving distributed learning methodology, has been impeded by the challenge of high communication overheads, typica…
DoctorGLM: Fine-tuning your Chinese Doctor is not a Herculean Task
Honglin Xiong, Sheng Wang, Yitao Zhu +5
The recent progress of large language models (LLMs), including ChatGPT and GPT-4, in comprehending and responding to human instructions has been remarkable. Nevertheless, these mod…
S2CTrans: Building a bridge from SPARQL to Cypher
Zihao Zhao, Xiaodong Ge, Zhihong Shen
In graph data applications, data is primarily maintained using two models: RDF (Resource Description Framework) and property graph. The property graph model is widely adopted by in…
ChatCAD: Interactive Computer-Aided Diagnosis on Medical Image using Large Language Models
Sheng Wang, Zihao Zhao, Xi Ouyang +2
Large language models (LLMs) have recently demonstrated their potential in clinical applications, providing valuable medical knowledge and advice. For example, a large dialog LLM l…
Load-balanced Gather-scatter Patterns for Sparse Deep Neural Networks
Fei Sun, Minghai Qin, Tianyun Zhang +6
Deep neural networks (DNNs) have been proven to be effective in solving many real-life problems, but its high computation cost prohibits those models from being deployed to edge de…