Tu Dinh Nguyen

Publication Activity (10 Years)

Years Active: 2013-2022
Publications (10 Years): 58

Top Topics

Support Vector Machine

Graph Embedding

Kernel Learning

Boltzmann Machines

Top Venues

Publications

Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Q. Phung
Universal Graph Transformer Self-Attention Networks. WWW (Companion Volume) (2022)
Khanh Nguyen, Trung Le, Tu Dinh Nguyen, Geoffrey I. Webb, Dinh Phung
Robust Variational Learning for Multiclass Kernel Models With Stein Refinement. IEEE Trans. Knowl. Data Eng. 34 (9) (2022)
Dai Quoc Nguyen, Thanh Vu, Tu Dinh Nguyen, Dinh Q. Phung
QuatRE: Relation-Aware Quaternions for Knowledge Graph Embeddings. WWW (Companion Volume) (2022)
Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Q. Phung
Quaternion Graph Neural Networks. ACML (2021)
Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung
Quaternion Graph Neural Networks. CoRR (2020)
Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung
A Self-Attention Network based Node Embedding Model. CoRR (2020)
Dai Quoc Nguyen, Thanh Vu, Tu Dinh Nguyen, Dinh Phung
QuatRE: Relation-Aware Quaternions for Knowledge Graph Embeddings. CoRR (2020)
Dai Quoc Nguyen, Tu Dinh Nguyen, Dat Quoc Nguyen, Dinh Phung
A Capsule Network-based Model for Learning Node Embeddings. CIKM (2020)
Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung
A Self-attention Network Based Node Embedding Model. ECML/PKDD (3) (2020)
Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Q. Phung
Relational Memory-based Knowledge Graph Embedding. CoRR (2019)
Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung
Unsupervised Universal Self-Attention Network for Graph Classification. CoRR (2019)
Trung Le, Quan Hoang, Hung Vu, Tu Dinh Nguyen, Hung Bui, Dinh Q. Phung
Learning Generative Adversarial Networks from Multiple Data Sources. IJCAI (2019)
Dai Quoc Nguyen, Tu Dinh Nguyen, Dat Quoc Nguyen, Dinh Phung
A Capsule Network-based Model for Learning Node Embeddings. CoRR (2019)
Hung Vu, Tu Dinh Nguyen, Trung Le, Wei Luo, Dinh Q. Phung
Robust Anomaly Detection in Videos Using Multilevel Representations. AAAI (2019)
Nhan Dam, Quan Hoang, Trung Le, Tu Dinh Nguyen, Hung Bui, Dinh Phung
Three-Player Wasserstein GAN via Amortised Duality. IJCAI (2019)
Trung Le, Khanh Nguyen, Vu Nguyen, Tu Dinh Nguyen, Dinh Q. Phung
GoGP: scalable geometric-based Gaussian process for online regression. Knowl. Inf. Syst. 60 (1) (2019)
Dai Quoc Nguyen, Dat Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung
A convolutional neural network-based model for knowledge base completion and its application to search personalization. Semantic Web 10 (5) (2019)
Dai Quoc Nguyen, Thanh Vu, Tu Dinh Nguyen, Dat Quoc Nguyen, Dinh Q. Phung
A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Personalization. NAACL-HLT (1) (2019)
Dai Quoc Nguyen, Tu Dinh Nguyen, Dat Quoc Nguyen, Dinh Q. Phung
A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network. NAACL-HLT (2) (2018)
Trung Le, Hung Vu, Tu Dinh Nguyen, Dinh Q. Phung
Geometric Enclosing Networks. IJCAI (2018)
Dang Nguyen, Tu Dinh Nguyen, Wei Luo, Svetha Venkatesh
Trans2Vec: Learning Transaction Embedding via Items and Frequent Itemsets. PAKDD (3) (2018)
Dang Nguyen, Wei Luo, Tu Dinh Nguyen, Svetha Venkatesh, Dinh Q. Phung
Learning Graph Representation via Frequent Subgraphs. SDM (2018)
Khanh Nguyen, Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, Geoffrey I. Webb
Robust Bayesian Kernel Machine via Stein Variational Gradient Descent for Big Data. KDD (2018)
Khanh Nguyen, Trung Le, Tu Dinh Nguyen, Dinh Q. Phung
Bayesian Multi-Hyperplane Machine for Pattern Recognition. ICPR (2018)
Dai Quoc Nguyen, Thanh Vu, Tu Dinh Nguyen, Dat Quoc Nguyen, Dinh Q. Phung
A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Personalization. CoRR (2018)
Quan Hoang, Tu Dinh Nguyen, Trung Le, Dinh Q. Phung
MGAN: Training Generative Adversarial Nets with Multiple Generators. ICLR (Poster) (2018)
Khanh Nguyen, Nhan Dam, Trung Le, Tu Dinh Nguyen, Dinh Q. Phung
Clustering Induced Kernel Learning. ACML (2018)
Hung Vu, Tu Dinh Nguyen, Dinh Q. Phung
Detection of Unknown Anomalies in Streaming Videos with Generative Energy-based Boltzmann Models. CoRR (2018)
Dang Nguyen, Wei Luo, Tu Dinh Nguyen, Svetha Venkatesh, Dinh Q. Phung
Sqn2Vec: Learning Sequence Representation via Sequential Patterns with a Gap Constraint. ECML/PKDD (2) (2018)
Hung Vu, Tu Dinh Nguyen, Trung Le, Wei Luo, Dinh Q. Phung
Batch Normalized Deep Boltzmann Machines. ACML (2018)
Tu Dinh Nguyen, Trung Le, Hung Vu, Dinh Q. Phung
Dual Discriminator Generative Adversarial Nets. NIPS (2017)
Hung Vu, Tu Dinh Nguyen, Anthony Travers, Svetha Venkatesh, Dinh Q. Phung
Energy-Based Localized Anomaly Detection in Video Surveillance. PAKDD (1) (2017)
Quan Hoang, Tu Dinh Nguyen, Trung Le, Dinh Q. Phung
Multi-Generator Generative Adversarial Nets. CoRR (2017)
Trung Le, Tu Dinh Nguyen, Vu Nguyen, Dinh Q. Phung
Approximation Vector Machines for Large-scale Online Learning. J. Mach. Learn. Res. 18 (2017)
Hung Nguyen, Sarah J. Maclagan, Tu Dinh Nguyen, Thin Nguyen, Paul Flemons, Kylie Andrews, Euan G. Ritchie, Dinh Q. Phung
Animal Recognition and Identification with Deep Convolutional Neural Networks for Automated Wildlife Monitoring. DSAA (2017)
Trung Le, Tu Dinh Nguyen, Dinh Q. Phung
KGAN: How to Break The Minimax Game in GAN. CoRR (2017)
Trung Le, Khanh Nguyen, Vu Nguyen, Tu Dinh Nguyen, Dinh Q. Phung
GoGP: Fast Online Regression with Gaussian Processes. ICDM (2017)
Dai Quoc Nguyen, Tu Dinh Nguyen, Dat Quoc Nguyen, Dinh Q. Phung
A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network. CoRR (2017)
Trung Le, Khanh Nguyen, Tu Dinh Nguyen, Dinh Q. Phung
Analogical-based Bayesian Optimization. CoRR (2017)
Tu Dinh Nguyen, Trung Le, Hung Bui, Dinh Q. Phung
Large-scale Online Kernel Learning with Random Feature Reparameterization. IJCAI (2017)
Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
Nonnegative Restricted Boltzmann Machines for Parts-based Representations Discovery and Predictive Model Stabilization. CoRR (2017)
Hung Vu, Dinh Q. Phung, Tu Dinh Nguyen, Anthony Trevors, Svetha Venkatesh
Energy-based Models for Video Anomaly Detection. CoRR (2017)
Tu Dinh Nguyen, Dinh Q. Phung, Viet Huynh, Trung Le
Supervised Restricted Boltzmann Machines. UAI (2017)
Tu Dinh Nguyen, Trung Le, Hung Vu, Dinh Q. Phung
Dual Discriminator Generative Adversarial Nets. CoRR (2017)
Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
Statistical Latent Space Approach for Mixed Data Modelling and Applications. CoRR (2017)
Trung Le, Hung Vu, Tu Dinh Nguyen, Dinh Q. Phung
Geometric Enclosing Networks. CoRR (2017)
Trung Le, Tu Dinh Nguyen, Vu Nguyen, Dinh Q. Phung
Dual Space Gradient Descent for Online Learning. NIPS (2016)
Khanh Nguyen, Trung Le, Vu Nguyen, Tu Dinh Nguyen, Dinh Q. Phung
Multiple Kernel Learning with Data Augmentation. ACML (2016)
Trung Le, Tu Dinh Nguyen, Vu Nguyen, Dinh Q. Phung
Approximation Vector Machines for Large-scale Online Learning. CoRR (2016)
Trung Le, Phuong Duong, Mi Dinh, Tu Dinh Nguyen, Vu Nguyen, Dinh Q. Phung
Budgeted Semi-supervised Support Vector Machine . UAI (2016)
Tu Dinh Nguyen, Vu Nguyen, Trung Le, Dinh Q. Phung
Distributed data augmented support vector machine on Spark. ICPR (2016)
Trung Le, Vu Nguyen, Tu Dinh Nguyen, Dinh Q. Phung
Nonparametric Budgeted Stochastic Gradient Descent. AISTATS (2016)
Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
Graph-induced restricted Boltzmann machines for document modeling. Inf. Sci. 328 (2016)
Vu Nguyen, Tu Dinh Nguyen, Trung Le, Svetha Venkatesh, Dinh Q. Phung
One-Pass Logistic Regression for Label-Drift and Large-Scale Classification on Distributed Systems. ICDM (2016)
Truyen Tran, Tu Dinh Nguyen, Dinh Q. Phung, Svetha Venkatesh
Learning vector representation of medical objects via EMR-driven nonnegative restricted Boltzmann machines (eNRBM). J. Biomed. Informatics 54 (2015)
Shivapratap Gopakumar, Truyen Tran, Tu Dinh Nguyen, Dinh Q. Phung, Svetha Venkatesh
Stabilizing High-Dimensional Prediction Models Using Feature Graphs. IEEE J. Biomed. Health Informatics 19 (3) (2015)
Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
Tensor-Variate Restricted Boltzmann Machines. AAAI (2015)
Shivapratap Gopakumar, Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
Stabilizing Sparse Cox Model Using Statistic and Semantic Structures in Electronic Medical Records. PAKDD (2) (2015)
Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
Latent Patient Profile Modelling and Applications with Mixed-Variate Restricted Boltzmann Machine. PAKDD (1) (2013)
Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
Learning Parts-based Representations with Nonnegative Restricted Boltzmann Machine. ACML (2013)
Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh
Learning sparse latent representation and distance metric for image retrieval. ICME (2013)