1 code implementation • ICML 2017 • Nhat Ho, XuanLong Nguyen, Mikhail Yurochkin, Hung Hai Bui, Viet Huynh, Dinh Phung
We propose a novel approach to the problem of multilevel clustering, which aims to simultaneously partition data in each group and discover grouping patterns among groups in a potentially large hierarchically structured corpus of data.
no code implementations • 29 Oct 2018 • Nhat Ho, Viet Huynh, Dinh Phung, Michael. I. Jordan
We propose a novel probabilistic approach to multilevel clustering problems based on composite transportation distance, which is a variant of transportation distance where the underlying metric is Kullback-Leibler divergence.
1 code implementation • 19 Sep 2019 • Viet Huynh, Nhat Ho, Nhan Dam, XuanLong Nguyen, Mikhail Yurochkin, Hung Bui, and Dinh Phung
We propose a novel approach to the problem of multilevel clustering, which aims to simultaneously partition data in each group and discover grouping patterns among groups in a potentially large hierarchically structured corpus of data.
no code implementations • 10 Oct 2019 • Tam Le, Viet Huynh, Nhat Ho, Dinh Phung, Makoto Yamada
We study in this paper a variant of Wasserstein barycenter problem, which we refer to as tree-Wasserstein barycenter, by leveraging a specific class of ground metrics, namely tree metrics, for Wasserstein distance.
1 code implementation • 16 Apr 2020 • Mahmoud Hossam, Trung Le, Viet Huynh, Michael Papasimeon, Dinh Phung
One of the challenging problems in sequence generation tasks is the optimized generation of sequences with specific desired goals.
1 code implementation • ICLR 2021 • He Zhao, Dinh Phung, Viet Huynh, Trung Le, Wray Buntine
Recently, Neural Topic Models (NTMs) inspired by variational autoencoders have obtained increasingly research interest due to their promising results on text analysis.
Ranked #5 on Topic Models on 20NewsGroups
no code implementations • NeurIPS 2020 • Viet Huynh, He Zhao, Dinh Phung
We present an optimal transport framework for learning topics from textual data.
no code implementations • 28 Feb 2021 • He Zhao, Dinh Phung, Viet Huynh, Yuan Jin, Lan Du, Wray Buntine
Topic modelling has been a successful technique for text analysis for almost twenty years.
no code implementations • 27 Apr 2021 • Mahmoud Hossam, Trung Le, Michael Papasimeon, Viet Huynh, Dinh Phung
Generating realistic sequences is a central task in many machine learning applications.
no code implementations • 27 Apr 2021 • Mahmoud Hossam, Trung Le, He Zhao, Viet Huynh, Dinh Phung
There has been recently a growing interest in studying adversarial examples on natural language models in the black-box setting.