892 citations · 1.1k across the 17 of their papers we have counts for
9 papers · 1 filter
A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network
Dai Quoc Nguyen, Tu Dinh Nguyen, Dat Quoc Nguyen +1
In this paper, we propose a novel embedding model, named ConvKB, for knowledge base completion. Our model ConvKB advances state-of-the-art models by employing a convolutional neura…
KGAN: How to Break The Minimax Game in GAN
Trung Le, Tu Dinh Nguyen, Dinh Phung
Generative Adversarial Networks (GANs) were intuitively and attractively explained under the perspective of game theory, wherein two involving parties are a discriminator and a gen…
Analogical-based Bayesian Optimization
Trung Le, Khanh Nguyen, Tu Dinh Nguyen +1
Some real-world problems revolve to solve the optimization problem \max_{x\in\mathcal{X}}f\left(x\right) where f\left(.\right) is a black-box function and X might be the set of non…
Dual Discriminator Generative Adversarial Nets
Tu Dinh Nguyen, Trung Le, Hung Vu +1
We propose in this paper a novel approach to tackle the problem of mode collapse encountered in generative adversarial network (GAN). Our idea is intuitive but proven to be very ef…
Nonnegative Restricted Boltzmann Machines for Parts-based Representations Discovery and Predictive Model Stabilization
Tu Dinh Nguyen, Truyen Tran, Dinh Phung +1
The success of any machine learning system depends critically on effective representations of data. In many cases, it is desirable that a representation scheme uncovers the parts-b…
Statistical Latent Space Approach for Mixed Data Modelling and Applications
Tu Dinh Nguyen, Truyen Tran, Dinh Phung +1
The analysis of mixed data has been raising challenges in statistics and machine learning. One of two most prominent challenges is to develop new statistical techniques and methodo…
Energy-based Models for Video Anomaly Detection
Hung Vu, Dinh Phung, Tu Dinh Nguyen +2
Automated detection of abnormalities in data has been studied in research area in recent years because of its diverse applications in practice including video surveillance, industr…
Geometric Enclosing Networks
Trung Le, Hung Vu, Tu Dinh Nguyen +1
Training model to generate data has increasingly attracted research attention and become important in modern world applications. We propose in this paper a new geometry-based optim…
Multi-Generator Generative Adversarial Nets
Quan Hoang, Tu Dinh Nguyen, Trung Le +1
We propose a new approach to train the Generative Adversarial Nets (GANs) with a mixture of generators to overcome the mode collapsing problem. The main intuition is to employ mult…