14 citations · 125 across the 88 of their papers we have counts for
11 papers · 1 filter
Two-view Graph Neural Networks for Knowledge Graph Completion
Vinh Tong, Dai Quoc Nguyen, Dinh Phung +1
We present an effective graph neural network (GNN)-based knowledge graph embedding model, which we name WGE, to capture entity- and relation-focused graph structures. Given a knowl…
On Learning Domain-Invariant Representations for Transfer Learning with Multiple Sources
Trung Phung, Trung Le, Long Vuong +4
Domain adaptation (DA) benefits from the rigorous theoretical works that study its insightful characteristics and various aspects, e.g., learning domain-invariant representations a…
On Cross-Layer Alignment for Model Fusion of Heterogeneous Neural Networks
Dang Nguyen, Trang Nguyen, Khai Nguyen +3
Layer-wise model fusion via optimal transport, named OTFusion, applies soft neuron association for unifying different pre-trained networks to save computational resources. While en…
On Label Shift in Domain Adaptation via Wasserstein Distance
Trung Le, Dat Do, Tuan Nguyen +4
We study the label shift problem between the source and target domains in general domain adaptation (DA) settings. We consider transformations transporting the target to source dom…
ReGVD: Revisiting Graph Neural Networks for Vulnerability Detection
Van-Anh Nguyen, Dai Quoc Nguyen, Van Nguyen +3
Identifying vulnerabilities in the source code is essential to protect the software systems from cyber security attacks. It, however, is also a challenging step that requires speci…
Rapid Elastic Architecture Search under Specialized Classes and Resource Constraints
Jing Liu, Bohan Zhuang, Mingkui Tan +4
In many real-world applications, we often need to handle various deployment scenarios, where the resource constraint and the superclass of interest corresponding to a group of clas…
Improved and Efficient Text Adversarial Attacks using Target Information
Mahmoud Hossam, Trung Le, He Zhao +2
There has been recently a growing interest in studying adversarial examples on natural language models in the black-box setting. These methods attack natural language classifiers b…
Node Co-occurrence based Graph Neural Networks for Knowledge Graph Link Prediction
Dai Quoc Nguyen, Vinh Tong, Dinh Phung +1
We introduce a novel embedding model, named NoGE, which aims to integrate co-occurrence among entities and relations into graph neural networks to improve knowledge graph completio…
Bridging Global Context Interactions for High-Fidelity Image Completion
Chuanxia Zheng, Tat-Jen Cham, Jianfei Cai +1
Bridging global context interactions correctly is important for high-fidelity image completion with large masks. Previous methods attempting this via deep or large receptive field…
On Transportation of Mini-batches: A Hierarchical Approach
Khai Nguyen, Dang Nguyen, Quoc Nguyen +5
Mini-batch optimal transport (m-OT) has been successfully used in practical applications that involve probability measures with a very high number of supports. The m-OT solves seve…
Understanding and Achieving Efficient Robustness with Adversarial Supervised Contrastive Learning
Anh Bui, Trung Le, He Zhao +3
Contrastive learning (CL) has recently emerged as an effective approach to learning representation in a range of downstream tasks. Central to this approach is the selection of posi…