892 citations · 2.3k across the 60 of their papers we have counts for
15 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…