Dinh Phung

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A Self-Attention Network based Node Embedding Model pdf

Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Q. Phung, 2020, ECML/PKDD.

Robust Anomaly Detection in Videos Using Multilevel Representations

Wei Luo, Trung Le, Dinh Q. Phung, 2019, AAAI.

An effective spatial-temporal attention based neural network for traffic flow prediction

Hai Le Vu, Zhiyuan Liu, Dinh Q. Phung, 2019, Transportation Research Part C: Emerging Technologies.

A matrix factorization framework for jointly analyzing multiple nonnegative data sources

Svetha Venkatesh, Brett Adams, Dinh Q. Phung, 2011, SDM 2011.

Universal Self-Attention Network for Graph Classification

Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Q. Phung, 2019 .

BYou Tube and I Find(VPersonalizing Multimedia Content Access To help users find material of interest in large multimedia collections, researchers are exploring techniques to allow authors to easily capture effective descriptive data, and methods for modeling user preferences.

Svetha Venkatesh, Chitra Dorai, Brett Adams, 2008 .

Maximal Divergence Sequential Autoencoder for Binary Software Vulnerability Detection

Tuan Nguyen, Trung Le, Lizhen Qu, 2019, ICLR.

Perturbations are not Enough: Generating Adversarial Examples with Spatial Distortions pdf

He Zhao, Dinh Q. Phung, Tamas Abraham, 2019, ArXiv.

A Capsule Network-based Model for Learning Node Embeddings

Dai Quoc Nguyen, Tu Dinh Nguyen, Dat Quoc Nguyen, 2020, CIKM.

Dual-Component Deep Domain Adaptation: A New Approach for Cross Project Software Vulnerability Detection

Dinh Q. Phung, Dinh Phung, Trung Thanh Le, 2020, PAKDD.

Improving Adversarial Robustness by Enforcing Local and Global Compactness

Trung Le, Dinh Q. Phung, Tamas Abraham, 2020, ECCV.

Advances in Knowledge Discovery and Data Mining

Geoffrey I. Webb, Vincent S. Tseng, Dinh Q. Phung, 2018, Lecture Notes in Computer Science.

Volume 39: proceedings of the sixth Asian conference on machine learning

Dinh Phung, Hang Li, 2015, ACML 2015.

Learning Latent Activities from Social Signals with Hierarchical Dirichlet Processes

Dinh Q. Phung, Sunil Gupta, Svetha Venkatesh, 2014 .

A convolutional neural network-based model for knowledge base completion and its application to search personalization

Dai Quoc Nguyen, Tu Dinh Nguyen, Dat Quoc Nguyen, 2019, Semantic Web.

Relational Memory-based Knowledge Graph Embedding pdf

Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Q. Phung, 2019, ArXiv.

Learning How to Active Learn by Dreaming

Gholamreza Haffari, Dinh Q. Phung, Dinh Phung, 2019, ACL.

PC chairs’ preface

Vincent S. Tseng, Dinh Phung, 2018, KDD 2018.

Advances in Knowledge Discovery and Data Mining

Geoffrey I. Webb, Vincent S. Tseng, Lida Rashidi, 2018, Lecture Notes in Computer Science.

Predicting healthcare trajectories from medical records: A deep learning approach

Truyen Tran, Dinh Q. Phung, Svetha Venkatesh, 2017, J. Biomed. Informatics.

Parameterized Rate-Distortion Stochastic Encoder

Trung Le, Dinh Q. Phung, Dinh Phung, 2020, ICML.

Deep Domain Adaptation for Vulnerable Code Function Identification

Lizhen Qu, Dinh Q. Phung, Paul Montague, 2019, 2019 International Joint Conference on Neural Networks (IJCNN).

Pair-based Uncertainty and Diversity Promoting Early Active Learning for Person Re-identification

Xiaoqin Zhang, Xiaojun Chang, Yi Yang, 2020, ACM Trans. Intell. Syst. Technol..

A matrix factorization framework for jointly analyzing multiple nonnegative data sources

Svetha Venkatesh, Brett Adams, Dinh Phung, 2011, SDM 2011.

Scalable Semi-supervised Learning with Graph-based Kernel Machine

Dinh Phung, Vu Nguyen, Khanh Nguyen, 2016 .

Continuous discovery of co-location contexts from Bluetooth data

Svetha Venkatesh, Dinh Q. Phung, Dinh Phung, 2015 .

Understanding and Achieving Efficient Robustness with Adversarial Contrastive Learning

Trung Le, Dinh Q. Phung, Seyit Camtepe, 2021, ArXiv.

On Scalable Variant of Wasserstein Barycenter pdf

Makoto Yamada, Dinh Q. Phung, Nhat Ho, 2019, ArXiv.

Bayesian Nonparametric Approaches to Abnormality Detection in Video Surveillance

Svetha Venkatesh, Duc-Son Pham, Dinh Phung, 2015 .

Advances in Knowledge Discovery and Data Mining

Geoffrey I. Webb, Vincent S. Tseng, Lida Rashidi, 2018, Lecture Notes in Computer Science.

Tree-Wasserstein Barycenter for Large-Scale Multilevel Clustering and Scalable Bayes.

Makoto Yamada, Dinh Q. Phung, Nhat Ho, 2019, 1910.04483.

A study on the stability of EEG signals for user authentication

Wanli Ma, Dinh Q. Phung, Dinh Phung, 2015, 2015 7th International IEEE/EMBS Conference on Neural Engineering (NER).

Unsupervised Universal Self-Attention Network for Graph Classification pdf

Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Q. Phung, 2019, ArXiv.

GoGP: scalable geometric-based Gaussian process for online regression

Trung Le, Tu Dinh Nguyen, Khanh Nguyen, 2018, Knowledge and Information Systems.

MED-TEX: Transferring and Explaining Knowledge with Less Data from Pretrained Medical Imaging Models pdf

Jianfei Cai, Dinh Phung, Thanh Nguyen-Duc, 2020, ArXiv.

OptiGAN: Generative Adversarial Networks for Goal Optimized Sequence Generation

Trung Le, Dinh Q. Phung, Michael Papasimeon, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

Using spatiotemporal distribution of geocoded Twitter data to predict US county-level health indices

John Yearwood, Duc Thanh Nguyen, Svetha Venkatesh, 2020, Future Gener. Comput. Syst..

Learning graph representation via frequent subgraphs

Svetha Venkatesh, Tu Dinh Nguyen, Dang Nguyen, 2018 .

Text Generation with Deep Variational GAN pdf

Trung Le, Dinh Q. Phung, Michael Papasimeon, 2021, ArXiv.

BoMb-OT: On Batch of Mini-batches Optimal Transport pdf

Trung Le, Tung Pham, Khai Nguyen, 2021, ArXiv.

Topic Model Kernel Classification With Probabilistically Reduced Features

Svetha Venkatesh, Dinh Phung, Vu Nguyen, 2021 .

Topic Modelling Meets Deep Neural Networks: A Survey pdf

Dinh Q. Phung, Lan Du, Dinh Phung, 2021, IJCAI.

Speed up health research through topic modeling of coded clinical data

Svetha Venkatesh, Truyen Tran, Dinh Phung, 2014 .

Large Sample Asymptotic for Nonparametric Mixture Model with Count Data

Trung Le, Svetha Venkatesh, Dinh Phung, 2015 .

Sparkling Vector Machines

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2015 .

TOBY play-pad application to teach children with ASD – A pilot trial

Svetha Venkatesh, Dinh Q. Phung, Thi Duong, 2013, Developmental neurorehabilitation.