Search Results for author: Van Nguyen

Found 16 papers, 6 papers with code

A Class-aware Optimal Transport Approach with Higher-Order Moment Matching for Unsupervised Domain Adaptation

no code implementations29 Jan 2024 Tuan Nguyen, Van Nguyen, Trung Le, He Zhao, Quan Hung Tran, Dinh Phung

Additionally, we propose minimizing class-aware Higher-order Moment Matching (HMM) to align the corresponding class regions on the source and target domains.

Unsupervised Domain Adaptation

Learning to Quantize Vulnerability Patterns and Match to Locate Statement-Level Vulnerabilities

1 code implementation26 May 2023 Michael Fu, Trung Le, Van Nguyen, Chakkrit Tantithamthavorn, Dinh Phung

Prior studies found that vulnerabilities across different vulnerable programs may exhibit similar vulnerable scopes, implicitly forming discernible vulnerability patterns that can be learned by DL models through supervised training.

Vulnerability Detection

Few-shot Domain-Adaptive Visually-fused Event Detection from Text

no code implementations4 May 2023 Farhad Moghimifar, Fatemeh Shiri, Van Nguyen, Reza Haffari, Yuan-Fang Li

In this paper, we present a novel domain-adaptive visually-fused event detection approach that can be trained on a few labelled image-text paired data points.

Event Detection

Toward the Automated Construction of Probabilistic Knowledge Graphs for the Maritime Domain

no code implementations4 May 2023 Fatemeh Shiri, Teresa Wang, Shirui Pan, Xiaojun Chang, Yuan-Fang Li, Reza Haffari, Van Nguyen, Shuang Yu

In order to exploit the potentially useful and rich information from such sources, it is necessary to extract not only the relevant entities and concepts but also their semantic relations, together with the uncertainty associated with the extracted knowledge (i. e., in the form of probabilistic knowledge graphs).

Knowledge Graphs

Application of Knowledge Distillation to Multi-task Speech Representation Learning

no code implementations29 Oct 2022 Mine Kerpicci, Van Nguyen, Shuhua Zhang, Erik Visser

Model architectures such as wav2vec 2. 0 and HuBERT have been proposed to learn speech representations from audio waveforms in a self-supervised manner.

Keyword Spotting Knowledge Distillation +4

Feature-based Learning for Diverse and Privacy-Preserving Counterfactual Explanations

1 code implementation27 Sep 2022 Vy Vo, Trung Le, Van Nguyen, He Zhao, Edwin Bonilla, Gholamreza Haffari, Dinh Phung

Interpretable machine learning seeks to understand the reasoning process of complex black-box systems that are long notorious for lack of explainability.

counterfactual feature selection +3

Cross Project Software Vulnerability Detection via Domain Adaptation and Max-Margin Principle

1 code implementation19 Sep 2022 Van Nguyen, Trung Le, Chakkrit Tantithamthavorn, John Grundy, Hung Nguyen, Dinh Phung

However, there are still two open and significant issues for SVD in terms of i) learning automatic representations to improve the predictive performance of SVD, and ii) tackling the scarcity of labeled vulnerabilities datasets that conventionally need laborious labeling effort by experts.

Domain Adaptation Representation Learning +2

An Additive Instance-Wise Approach to Multi-class Model Interpretation

1 code implementation7 Jul 2022 Vy Vo, Van Nguyen, Trung Le, Quan Hung Tran, Gholamreza Haffari, Seyit Camtepe, Dinh Phung

A popular attribution-based approach is to exploit local neighborhoods for learning instance-specific explainers in an additive manner.

Additive models Interpretable Machine Learning

Paraphrasing Techniques for Maritime QA system

no code implementations21 Mar 2022 Fatemeh Shiri, Terry Yue Zhuo, Zhuang Li, Van Nguyen, Shirui Pan, Weiqing Wang, Reza Haffari, Yuan-Fang Li

In this paper, we investigate how to exploit paraphrasing methods for the automated generation of large-scale training datasets (in the form of paraphrased utterances and their corresponding logical forms in SQL format) and present our experimental results using real-world data in the maritime domain.

ReGVD: Revisiting Graph Neural Networks for Vulnerability Detection

1 code implementation14 Oct 2021 Van-Anh Nguyen, Dai Quoc Nguyen, Van Nguyen, Trung Le, Quan Hung Tran, Dinh Phung

Identifying vulnerabilities in the source code is essential to protect the software systems from cyber security attacks.

Graph Embedding text-classification +2

Multi-task Voice Activated Framework using Self-supervised Learning

no code implementations3 Oct 2021 Shehzeen Hussain, Van Nguyen, Shuhua Zhang, Erik Visser

Finally, we extend our framework to perform multi-task learning by jointly optimizing the network parameters on multiple voice activated tasks using a shared transformer backbone.

Emotion Classification Keyword Spotting +5

Fine-grained Software Vulnerability Detection via Information Theory and Contrastive Learning

no code implementations29 Sep 2021 Van Nguyen, Trung Le, John C. Grundy, Dinh Phung

Software vulnerabilities existing in a program or function of computer systems have been becoming a serious and crucial concern.

Contrastive Learning Representation Learning +1

Experimenting with robotic intra-logistics domains

no code implementations26 Apr 2018 Martin Gebser, Philipp Obermeier, Thomas Otto, Torsten Schaub, Orkunt Sabuncu, Van Nguyen, Tran Cao Son

More precisely, asprilo consists of a versatile benchmark generator, solution checker and visualizer as well as a bunch of reference encodings featuring various ASP techniques.

Benchmarking valid

Scalable Semi-supervised Learning with Graph-based Kernel Machine

no code implementations22 Jun 2016 Trung Le, Khanh Nguyen, Van Nguyen, Vu Nguyen, Dinh Phung

Acquiring labels are often costly, whereas unlabeled data are usually easy to obtain in modern machine learning applications.

BIG-bench Machine Learning

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