10 citations · 22 across the 6 of their papers we have counts for
7 papers
Image Feature Fusion-based Federated Client Unlearning (FCU)
Hangyi Shen, Yizhi Pan, Tiansuo Li +2
Major data protection regulations all mention the "right to be forgotten," and that's what pushed federated unlearning (FU) techniques forward. But one stubborn issue remains: cata…
PSRFlow: Probabilistic Super Resolution with Flow-Based Models for Scientific Data
Jingyi Shen, Han-Wei Shen
Although many deep-learning-based super-resolution approaches have been proposed in recent years, because no ground truth is available in the inference stage, few can quantify the…
SKG: A Versatile Information Retrieval and Analysis Framework for Academic Papers with Semantic Knowledge Graphs
Yamei Tu, Rui Qiu, Han-Wei Shen
The number of published research papers has experienced exponential growth in recent years, which makes it crucial to develop new methods for efficient and versatile information ex…
GNNInterpreter: A Probabilistic Generative Model-Level Explanation for Graph Neural Networks
Xiaoqi Wang, Han-Wei Shen
Recently, Graph Neural Networks (GNNs) have significantly advanced the performance of machine learning tasks on graphs. However, this technological breakthrough makes people wonder…
On the Importance and Applicability of Pre-Training for Federated Learning
Hong-You Chen, Cheng-Hao Tu, Ziwei Li +2
Pre-training is prevalent in nowadays deep learning to improve the learned model's performance. However, in the literature on federated learning (FL), neural networks are mostly in…
SmartGD: A GAN-Based Graph Drawing Framework for Diverse Aesthetic Goals
Xiaoqi Wang, Kevin Yen, Yifan Hu +1
While a multitude of studies have been conducted on graph drawing, many existing methods only focus on optimizing a single aesthetic aspect of graph layouts, which can lead to sub-…
Towards Self-Tuning Parameter Servers
Chris Liu, Pengfei Zhang, Bo Tang +4
Recent years, many applications have been driven advances by the use of Machine Learning (ML). Nowadays, it is common to see industrial-strength machine learning jobs that involve…