default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDTu Dinh Nguyen
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2022
[j7]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): 4425-4438 (2022)- [c36]Dai Quoc Nguyen, Thanh Vu, Tu Dinh Nguyen, Dinh Q. Phung:
QuatRE: Relation-Aware Quaternions for Knowledge Graph Embeddings. WWW (Companion Volume) 2022: 189-192 - [c35]Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Q. Phung:
Universal Graph Transformer Self-Attention Networks. WWW (Companion Volume) 2022: 193-196 - 2021
- [c34]Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Q. Phung:
Quaternion Graph Neural Networks. ACML 2021: 236-251 - 2020
- [c33]Dai Quoc Nguyen, Tu Dinh Nguyen, Dat Quoc Nguyen, Dinh Phung:
A Capsule Network-based Model for Learning Node Embeddings. CIKM 2020: 3313-3316 - [c32]Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung:
A Self-attention Network Based Node Embedding Model. ECML/PKDD (3) 2020: 364-377 - [i18]Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung:
A Self-Attention Network based Node Embedding Model. CoRR abs/2006.12100 (2020) - [i17]Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung:
Quaternion Graph Neural Networks. CoRR abs/2008.05089 (2020) - [i16]Dai Quoc Nguyen, Thanh Vu, Tu Dinh Nguyen, Dinh Phung:
QuatRE: Relation-Aware Quaternions for Knowledge Graph Embeddings. CoRR abs/2009.12517 (2020)
2010 – 2019
- 2019
- [j6]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): 197-226 (2019) - [j5]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): 947-960 (2019) - [c31]Hung Vu, Tu Dinh Nguyen, Trung Le, Wei Luo, Dinh Q. Phung:
Robust Anomaly Detection in Videos Using Multilevel Representations. AAAI 2019: 5216-5223 - [c30]Nhan Dam, Quan Hoang, Trung Le, Tu Dinh Nguyen, Hung Bui, Dinh Phung:
Three-Player Wasserstein GAN via Amortised Duality. IJCAI 2019: 2202-2208 - [c29]Trung Le, Quan Hoang, Hung Vu, Tu Dinh Nguyen, Hung Bui, Dinh Q. Phung:
Learning Generative Adversarial Networks from Multiple Data Sources. IJCAI 2019: 2823-2829 - [c28]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: 2180-2189 - [i15]Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Q. Phung:
Relational Memory-based Knowledge Graph Embedding. CoRR abs/1907.06080 (2019) - [i14]Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung:
Unsupervised Universal Self-Attention Network for Graph Classification. CoRR abs/1909.11855 (2019) - [i13]Dai Quoc Nguyen, Tu Dinh Nguyen, Dat Quoc Nguyen, Dinh Phung:
A Capsule Network-based Model for Learning Node Embeddings. CoRR abs/1911.04822 (2019) - 2018
- [c27]Khanh Nguyen, Nhan Dam, Trung Le, Tu Dinh Nguyen, Dinh Q. Phung:
Clustering Induced Kernel Learning. ACML 2018: 129-144 - [c26]Hung Vu, Tu Dinh Nguyen, Trung Le, Wei Luo, Dinh Q. Phung:
Batch Normalized Deep Boltzmann Machines. ACML 2018: 359-374 - [c25]Quan Hoang, Tu Dinh Nguyen, Trung Le, Dinh Q. Phung:
MGAN: Training Generative Adversarial Nets with Multiple Generators. ICLR (Poster) 2018 - [c24]Khanh Nguyen, Trung Le, Tu Dinh Nguyen, Dinh Q. Phung:
Bayesian Multi-Hyperplane Machine for Pattern Recognition. ICPR 2018: 609-614 - [c23]Trung Le, Hung Vu, Tu Dinh Nguyen, Dinh Q. Phung:
Geometric Enclosing Networks. IJCAI 2018: 2355-2361 - [c22]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: 2003-2011 - [c21]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: 327-333 - [c20]Dang Nguyen, Tu Dinh Nguyen, Wei Luo, Svetha Venkatesh:
Trans2Vec: Learning Transaction Embedding via Items and Frequent Itemsets. PAKDD (3) 2018: 361-372 - [c19]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: 569-584 - [c18]Dang Nguyen, Wei Luo, Tu Dinh Nguyen, Svetha Venkatesh, Dinh Q. Phung:
Learning Graph Representation via Frequent Subgraphs. SDM 2018: 306-314 - [i12]Hung Vu, Tu Dinh Nguyen, Dinh Q. Phung:
Detection of Unknown Anomalies in Streaming Videos with Generative Energy-based Boltzmann Models. CoRR abs/1805.01090 (2018) - [i11]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 abs/1808.04122 (2018) - 2017
- [j4]Trung Le, Tu Dinh Nguyen, Vu Nguyen, Dinh Q. Phung:
Approximation Vector Machines for Large-scale Online Learning. J. Mach. Learn. Res. 18: 111:1-111:55 (2017) - [c17]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: 40-49 - [c16]Trung Le, Khanh Nguyen, Vu Nguyen, Tu Dinh Nguyen, Dinh Q. Phung:
GoGP: Fast Online Regression with Gaussian Processes. ICDM 2017: 257-266 - [c15]Tu Dinh Nguyen, Trung Le, Hung Bui, Dinh Q. Phung:
Large-scale Online Kernel Learning with Random Feature Reparameterization. IJCAI 2017: 2543-2549 - [c14]Tu Dinh Nguyen, Trung Le, Hung Vu, Dinh Q. Phung:
Dual Discriminator Generative Adversarial Nets. NIPS 2017: 2670-2680 - [c13]Hung Vu, Tu Dinh Nguyen, Anthony Travers, Svetha Venkatesh, Dinh Q. Phung:
Energy-Based Localized Anomaly Detection in Video Surveillance. PAKDD (1) 2017: 641-653 - [c12]Tu Dinh Nguyen, Dinh Q. Phung, Viet Huynh, Trung Le:
Supervised Restricted Boltzmann Machines. UAI 2017 - [i10]Quan Hoang, Tu Dinh Nguyen, Trung Le, Dinh Q. Phung:
Multi-Generator Generative Adversarial Nets. CoRR abs/1708.02556 (2017) - [i9]Trung Le, Hung Vu, Tu Dinh Nguyen, Dinh Q. Phung:
Geometric Enclosing Networks. CoRR abs/1708.04733 (2017) - [i8]Hung Vu, Dinh Q. Phung, Tu Dinh Nguyen, Anthony Trevors, Svetha Venkatesh:
Energy-based Models for Video Anomaly Detection. CoRR abs/1708.05211 (2017) - [i7]Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Statistical Latent Space Approach for Mixed Data Modelling and Applications. CoRR abs/1708.05594 (2017) - [i6]Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Nonnegative Restricted Boltzmann Machines for Parts-based Representations Discovery and Predictive Model Stabilization. CoRR abs/1708.05603 (2017) - [i5]Tu Dinh Nguyen, Trung Le, Hung Vu, Dinh Q. Phung:
Dual Discriminator Generative Adversarial Nets. CoRR abs/1709.03831 (2017) - [i4]Trung Le, Khanh Nguyen, Tu Dinh Nguyen, Dinh Q. Phung:
Analogical-based Bayesian Optimization. CoRR abs/1709.06390 (2017) - [i3]Trung Le, Tu Dinh Nguyen, Dinh Q. Phung:
KGAN: How to Break The Minimax Game in GAN. CoRR abs/1711.01744 (2017) - [i2]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 abs/1712.02121 (2017) - 2016
- [j3]Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Graph-induced restricted Boltzmann machines for document modeling. Inf. Sci. 328: 60-75 (2016) - [c11]Khanh Nguyen, Trung Le, Vu Nguyen, Tu Dinh Nguyen, Dinh Q. Phung:
Multiple Kernel Learning with Data Augmentation. ACML 2016: 49-64 - [c10]Trung Le, Vu Nguyen, Tu Dinh Nguyen, Dinh Q. Phung:
Nonparametric Budgeted Stochastic Gradient Descent. AISTATS 2016: 654-572 - [c9]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: 1113-1118 - [c8]Tu Dinh Nguyen, Vu Nguyen, Trung Le, Dinh Q. Phung:
Distributed data augmented support vector machine on Spark. ICPR 2016: 498-503 - [c7]Trung Le, Tu Dinh Nguyen, Vu Nguyen, Dinh Q. Phung:
Dual Space Gradient Descent for Online Learning. NIPS 2016: 4583-4591 - [c6]Trung Le, Phuong Duong, Mi Dinh, Tu Dinh Nguyen, Vu Nguyen, Dinh Q. Phung:
Budgeted Semi-supervised Support Vector Machine . UAI 2016 - [i1]Trung Le, Tu Dinh Nguyen, Vu Nguyen, Dinh Q. Phung:
Approximation Vector Machines for Large-scale Online Learning. CoRR abs/1604.06518 (2016) - 2015
- [j2]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: 96-105 (2015) - [j1]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): 1044-1052 (2015) - [c5]Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Tensor-Variate Restricted Boltzmann Machines. AAAI 2015: 2887-2893 - [c4]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: 331-343 - 2013
- [c3]Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Learning Parts-based Representations with Nonnegative Restricted Boltzmann Machine. ACML 2013: 133-148 - [c2]Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh:
Learning sparse latent representation and distance metric for image retrieval. ICME 2013: 1-6 - [c1]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: 123-135
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-07 22:20 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
