50 citations · 69 across the 8 of their papers we have counts for
8 papers
TrustGuard: GNN-based Robust and Explainable Trust Evaluation with Dynamicity Support
Jie Wang, Zheng Yan, Jiahe Lan +2
Trust evaluation assesses trust relationships between entities and facilitates decision-making. Machine Learning (ML) shows great potential for trust evaluation owing to its learni…
LMC: Fast Training of GNNs via Subgraph Sampling with Provable Convergence
Zhihao Shi, Xize Liang, Jie Wang
The message passing-based graph neural networks (GNNs) have achieved great success in many real-world applications. However, training GNNs on large-scale graphs suffers from the we…
Deep learning numerical methods for high-dimensional fully nonlinear PIDEs and coupled FBSDEs with jumps
Wansheng Wang, Jie Wang, Jinping Li +2
We propose a deep learning algorithm for solving high-dimensional parabolic integro-differential equations (PIDEs) and high-dimensional forward-backward stochastic differential equ…
WeKws: A production first small-footprint end-to-end Keyword Spotting Toolkit
Jie Wang, Menglong Xu, Jingyong Hou +4
Keyword spotting (KWS) enables speech-based user interaction and gradually becomes an indispensable component of smart devices. Recently, end-to-end (E2E) methods have become the m…
Improving Pseudo Labels With Intra-Class Similarity for Unsupervised Domain Adaptation
Jie Wang, Xiao-Lei Zhang
Unsupervised domain adaptation (UDA) transfers knowledge from a label-rich source domain to a different but related fully-unlabeled target domain. To address the problem of domain…
TransRec: Learning Transferable Recommendation from Mixture-of-Modality Feedback
Jie Wang, Fajie Yuan, Mingyue Cheng +6
Learning large-scale pre-trained models on broad-ranging data and then transfer to a wide range of target tasks has become the de facto paradigm in many machine learning (ML) commu…
A Manifold Two-Sample Test Study: Integral Probability Metric with Neural Networks
Jie Wang, Minshuo Chen, Tuo Zhao +2
Two-sample tests are important areas aiming to determine whether two collections of observations follow the same distribution or not. We propose two-sample tests based on integral…
PAPooling: Graph-based Position Adaptive Aggregation of Local Geometry in Point Clouds
Jie Wang, Jianan Li, Lihe Ding +2
Fine-grained geometry, captured by aggregation of point features in local regions, is crucial for object recognition and scene understanding in point clouds. Nevertheless, existing…