42 citations · 73 across the 10 of their papers we have counts for
6 papers · 1 filter
Improved and Efficient Text Adversarial Attacks using Target Information
Mahmoud Hossam, Trung Le, He Zhao +2
There has been recently a growing interest in studying adversarial examples on natural language models in the black-box setting. These methods attack natural language classifiers b…
Text Generation with Deep Variational GAN
Mahmoud Hossam, Trung Le, Michael Papasimeon +2
Generating realistic sequences is a central task in many machine learning applications. There has been considerable recent progress on building deep generative models for sequence…
Topic Modelling Meets Deep Neural Networks: A Survey
He Zhao, Dinh Phung, Viet Huynh +3
Topic modelling has been a successful technique for text analysis for almost twenty years. When topic modelling met deep neural networks, there emerged a new and increasingly popul…
Artificial intelligence supported anemia control system (AISACS) to prevent anemia in maintenance hemodialysis patients
Toshiaki Ohara, Hiroshi Ikeda, Yoshiki Sugitani +5
Anemia, for which erythropoiesis-stimulating agents (ESAs) and iron supplements (ISs) are used as preventive measures, presents important difficulties for hemodialysis patients. Ne…
OptiGAN: Generative Adversarial Networks for Goal Optimized Sequence Generation
Mahmoud Hossam, Trung Le, Viet Huynh +2
One of the challenging problems in sequence generation tasks is the optimized generation of sequences with specific desired goals. Current sequential generative models mainly gener…
Probabilistic Multilevel Clustering via Composite Transportation Distance
Nhat Ho, Viet Huynh, Dinh Phung +1
We propose a novel probabilistic approach to multilevel clustering problems based on composite transportation distance, which is a variant of transportation distance where the unde…