T. Nguyen

发表

A Universal Self-Attention Graph Neural Network.

Dinh Q. Phung, D. Q. Nguyen, T. Nguyen, 2019 .

Sparkling Vector Machines

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

Learning Graph Representation via Frequent Subgraphs

Wei Luo, Svetha Venkatesh, Tu Dinh Nguyen, 2018, SDM.

Statistical Latent Space Approach for Mixed Data Modelling and Applications pdf

Svetha Venkatesh, Truyen Tran, Tu Dinh Nguyen, 2017, ArXiv.

Universal Graph Transformer Self-Attention Networks

Dinh Q. Phung, D. Q. Nguyen, T. Nguyen, 2019, WWW.

A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network pdf

Dai Quoc Nguyen, Tu Dinh Nguyen, Dat Quoc Nguyen, 2017, NAACL.

Geometric Enclosing Networks

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2017, IJCAI.

Learning vector representation of medical objects via EMR-driven nonnegative restricted Boltzmann machines (eNRBM)

Svetha Venkatesh, Truyen Tran, Tu Dinh Nguyen, 2015, J. Biomed. Informatics.

Clustering Induced Kernel Learning

Nhan Dam, Trung Le, Tu Dinh Nguyen, 2018, ACML.

Multiple Kernel Learning with Data Augmentation

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2016, ACML.

The Explicit Algebraic Reynolds Stress Models for Turbulent Flows

T. Nguyen, H. Phạm, 2012 .

A Relational Memory-based Embedding Model for Triple Classification and Search Personalization

Dinh Q. Phung, D. Q. Nguyen, T. Nguyen, 2019, ACL.

Quaternion Graph Neural Networks pdf

Dinh Phung, Dai Quoc Nguyen, Tu Dinh Nguyen, 2020, ACML.

Animal Recognition and Identification with Deep Convolutional Neural Networks for Automated Wildlife Monitoring

Tu Dinh Nguyen, Dinh Q. Phung, Hung Nguyen, 2017, 2017 IEEE International Conference on Data Science and Advanced Analytics (DSAA).

Approximation Vector Machines for Large-scale Online Learning

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2016, J. Mach. Learn. Res..

MGAN: Training Generative Adversarial Nets with Multiple Generators

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2018, ICLR.

Robust Anomaly Detection in Videos Using Multilevel Representations

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

A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Personalization pdf

Dai Quoc Nguyen, Tu Dinh Nguyen, Dat Quoc Nguyen, 2018, NAACL.

QuatRE: Relation-Aware Quaternions for Knowledge Graph Embeddings

Dinh Q. Phung, Thanh Vu, D. Q. Nguyen, 2020, WWW.

Sqn2Vec: Learning Sequence Representation via Sequential Patterns with a Gap Constraint

Wei Luo, Svetha Venkatesh, Tu Dinh Nguyen, 2018, ECML/PKDD.

Dual Discriminator Generative Adversarial Nets

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2017, NIPS.

Learning Generative Adversarial Networks from Multiple Data Sources

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2019, IJCAI.

Tensor-Variate Restricted Boltzmann Machines

Svetha Venkatesh, Truyen Tran, Tu Dinh Nguyen, 2015, AAAI.

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.

Three-Player Wasserstein GAN via Amortised Duality

Nhan Dam, Trung Le, Tu Dinh Nguyen, 2019, IJCAI.

One-Pass Logistic Regression for Label-Drift and Large-Scale Classification on Distributed Systems

Trung Le, Svetha Venkatesh, Tu Dinh Nguyen, 2016, 2016 IEEE 16th International Conference on Data Mining (ICDM).

Relational Memory-based Knowledge Graph Embedding pdf

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

Unsupervised Universal Self-Attention Network for Graph Classification pdf

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

A Capsule Network-based Model for Learning Node Embeddings

Dat Quoc Nguyen, Dinh Q. Phung, D. Q. Nguyen, 2019, CIKM.

Universal Self-Attention Network for Graph Classification

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

Energy-based Models for Video Anomaly Detection pdf

Svetha Venkatesh, Tu Dinh Nguyen, Dinh Q. Phung, 2017, ArXiv.

Multi-Generator Generative Adversarial Nets pdf

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2017, ArXiv.

Bayesian Multi-Hyperplane Machine for Pattern Recognition

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2018, 2018 24th International Conference on Pattern Recognition (ICPR).

Nonparametric Budgeted Stochastic Gradient Descent

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2016, AISTATS.

Dual Space Gradient Descent for Online Learning

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2016, NIPS.

Budgeted Semi-supervised Support Vector Machine

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2016, UAI.

Large-scale Online Kernel Learning with Random Feature Reparameterization

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2017, IJCAI.

A Capsule Network-based Embedding Model for Search Personalization pdf

Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Q. Phung, 2018, ArXiv.

A Self-Attention Network based Node Embedding Model pdf

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

Universal Graph Transformer Self-Attention Networks.

Dinh Q. Phung, D. Q. Nguyen, T. Nguyen, 2019 .

Trans2Vec: Learning Transaction Embedding via Items and Frequent Itemsets

Wei Luo, Svetha Venkatesh, Tu Dinh Nguyen, 2018, PAKDD.

Stabilizing Sparse Cox Model Using Statistic and Semantic Structures in Electronic Medical Records

Svetha Venkatesh, Truyen Tran, Tu Dinh Nguyen, 2015, PAKDD.

Nonnegative Restricted Boltzmann Machines for Parts-based Representations Discovery and Predictive Model Stabilization pdf

Svetha Venkatesh, Truyen Tran, Tu Dinh Nguyen, 2017, ArXiv.

Stabilizing High-Dimensional Prediction Models Using Feature Graphs

S. Venkatesh, T. Tran, Dinh Phung, 2015, IEEE Journal of Biomedical and Health Informatics.

Detection of Unknown Anomalies in Streaming Videos with Generative Energy-based Boltzmann Models pdf

Tu Dinh Nguyen, Dinh Q. Phung, Hung Vu, 2018, ArXiv.

Graph-induced restricted Boltzmann machines for document modeling

Svetha Venkatesh, Truyen Tran, Tu Dinh Nguyen, 2016, Inf. Sci..

Supervised Restricted Boltzmann Machines

Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, 2017, UAI.