← Authors

Tu Dinh Nguyen

15 papers · 2013–2021 · 8 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (8) πŸ—ΊοΈ Taxonomy Completionist (26) 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (9) 🌍 Conference Polyglot (8) 🀝 Dynamic Duo (15) 🧬 Topic Evolution πŸ’Ž Century Club (15) πŸš€ Conference Pioneer πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (65) ⚑ Prolific Year (5) πŸ”₯ Unstoppable (6)

Conferences

ACML (4) IJCAI (4) NAACL (2) AAAI (1) ACL (1) AISTATS (1) ICLR (1) JMLR (1)

Top co-authors

Dinh Phung (15) Trung Le (10) Dai Quoc Nguyen (4) Hung Vu (4) Hung Bui (3) Quan Hoang (3) Nhan Dam (2) Vu Nguyen (2) Wei Luo (2) Dat Quoc Nguyen (2)

Keywords

unsupervised learning (3) generative adversarial network (3) knowledge graph embedding (2) kernel online learning (2) generative model (2) feature learning (2) mode collapse (2) convolutional neural network (2) knowledge graph completion (2) stochastic gradient descent (2) hinge loss (2) optimal transport (1) graph classification (1) batch normalization (1) unsupervised clustering (1) link prediction (1) anomaly detection (1) feature representation (1) motion analysis (1) kernel approximation (1)

Papers

Quaternion Graph Neural Networks ACML 2021
A Relational Memory-based Embedding Model for Triple Classification and Search Personalization ACL 2020
Robust Anomaly Detection in Videos Using Multilevel Representations AAAI 2019
Three-Player Wasserstein GAN via Amortised Duality IJCAI 2019
Learning Generative Adversarial Networks from Multiple Data Sources IJCAI 2019
A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Personalization NAACL 2019
Geometric Enclosing Networks IJCAI 2018
MGAN: Training Generative Adversarial Nets with Multiple Generators ICLR 2018
A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network NAACL 2018
Clustering Induced Kernel Learning ACML 2018
Batch Normalized Deep Boltzmann Machines ACML 2018
Large-scale Online Kernel Learning with Random Feature Reparameterization IJCAI 2017
Approximation Vector Machines for Large-scale Online Learning JMLR 2017
Nonparametric Budgeted Stochastic Gradient Descent AISTATS 2016
Learning Parts-based Representations with Nonnegative Restricted Boltzmann Machine ACML 2013