activity
20192022
most citedComplicating the Social Networks for Better Storytelling: An Empirical Study of Chinese Historical Text and Novel

8 citations · 15 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV20223 cited

Social-DualCVAE: Multimodal Trajectory Forecasting Based on Social Interactions Pattern Aware and Dual Conditional Variational Auto-Encoder

Jiashi Gao, Xinming Shi, James J. Q. Yu

Pedestrian trajectory forecasting is a fundamental task in multiple utility areas, such as self-driving, autonomous robots, and surveillance systems. The future trajectory forecast…

cs.LG20214 cited

Resource-constrained Federated Edge Learning with Heterogeneous Data: Formulation and Analysis

Yi Liu, Yuanshao Zhu, James J. Q. Yu

Efficient collaboration between collaborative machine learning and wireless communication technology, forming a Federated Edge Learning (FEEL), has spawned a series of next-generat…

cs.SI20208 cited

Complicating the Social Networks for Better Storytelling: An Empirical Study of Chinese Historical Text and Novel

Chenhan Zhang

Digital humanities is an important subject because it enables developments in history, literature, and films. In this paper, we perform an empirical study of a Chinese historical t…

cs.LG2020

Privacy-preserving Traffic Flow Prediction: A Federated Learning Approach

Yi Liu, James J. Q. Yu, Jiawen Kang +2

Existing traffic flow forecasting approaches by deep learning models achieve excellent success based on a large volume of datasets gathered by governments and organizations. Howeve…

cs.LG2019

PPGAN: Privacy-preserving Generative Adversarial Network

Yi Liu, Jialiang Peng, James J. Q Yu +1

Generative Adversarial Network (GAN) and its variants serve as a perfect representation of the data generation model, providing researchers with a large amount of high-quality gene…