Tu Dinh Nguyen
15 papers · 2013–2021 · 8 conferences · across top CS/AI conferences
Achievements
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🌍 Conference Polyglot (8) 🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🏃 Academic Marathon (8)
🐣
Hot Topic Early Bird
🐝
Cross-Pollinator
(9)
🌍
Conference Polyglot
(8)
🤝
Dynamic Duo
(15)
🧬
Topic Evolution
💎
Century Club
(15)
🚀
Conference Pioneer
📈
Trend Setter
🗃️
Keyword Collector
(65)
⚡
Prolific Year
(5)
🔥
Unstoppable
(6)
Conferences
ACML (4)
IJCAI (4)
NAACL (2)
AAAI (1)
ACL (1)
AISTATS (1)
ICLR (1)
JMLR (1)
Top co-authors
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)
graph classification
(1)
unsupervised clustering
(1)
optimal transport
(1)
anomaly detection
(1)
link prediction
(1)
motion analysis
(1)
kernel approximation
(1)
probabilistic modeling
(1)
nonnegative matrix factorization
(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