213 citations · 264 across the 10 of their papers we have counts for
8 papers · 1 filter
Learning Data Teaching Strategies Via Knowledge Tracing
Ghodai Abdelrahman, Qing Wang
Teaching plays a fundamental role in human learning. Typically, a human teaching strategy would involve assessing a student's knowledge progress for tailoring the teaching material…
A Regularized Wasserstein Framework for Graph Kernels
Asiri Wijesinghe, Qing Wang, Stephen Gould
We propose a learning framework for graph kernels, which is theoretically grounded on regularizing optimal transport. This framework provides a novel optimal transport distance met…
Deep Graph Memory Networks for Forgetting-Robust Knowledge Tracing
Ghodai Abdelrahman, Qing Wang
Tracing a student's knowledge is vital for tailoring the learning experience. Recent knowledge tracing methods tend to respond to these challenges by modelling knowledge state dyna…
Beyond Low-Pass Filters: Adaptive Feature Propagation on Graphs
Sean Li, Dongwoo Kim, Qing Wang
Graph neural networks (GNNs) have been extensively studied for prediction tasks on graphs. As pointed out by recent studies, most GNNs assume local homophily, i.e., strong similari…
Knowledge Tracing with Sequential Key-Value Memory Networks
Ghodai Abdelrahman, Qing Wang
Can machines trace human knowledge like humans? Knowledge tracing (KT) is a fundamental task in a wide range of applications in education, such as massive open online courses (MOOC…
DFNets: Spectral CNNs for Graphs with Feedback-Looped Filters
Asiri Wijesinghe, Qing Wang
We propose a novel spectral convolutional neural network (CNN) model on graph structured data, namely Distributed Feedback-Looped Networks (DFNets). This model is incorporated with…
Learning to Sample: an Active Learning Framework
Jingyu Shao, Qing Wang, Fangbing Liu
Meta-learning algorithms for active learning are emerging as a promising paradigm for learning the ``best'' active learning strategy. However, current learning-based active learnin…
Collective Vertex Classification Using Recursive Neural Network
Qiongkai Xu, Qing Wang, Chenchen Xu +1
Collective classification of vertices is a task of assigning categories to each vertex in a graph based on both vertex attributes and link structure. Nevertheless, some existing ap…