Tu Dinh Nguyen

61 papers A* 9A 6B 3C 5Journal 25Unranked 13

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