892 citations · 2.3k across the 60 of their papers we have counts for
20 papers · 1 filter
Tree-Wasserstein Barycenter for Large-Scale Multilevel Clustering and Scalable Bayes
Tam Le, Viet Huynh, Nhat Ho +2
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…
On Efficient Multilevel Clustering via Wasserstein Distances
Viet Huynh, Nhat Ho, Nhan Dam +4
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 pote…
Multilevel Clustering via Wasserstein Means
Nhat Ho, XuanLong Nguyen, Mikhail Yurochkin +3
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 pote…
A Random Finite Set Model for Data Clustering
Dinh Phung, Ba-Ngu Bo
The goal of data clustering is to partition data points into groups to minimize a given objective function. While most existing clustering algorithms treat each data point as vecto…
Model-Based Multiple Instance Learning
Ba-Ngu Vo, Dinh Phung, Quang N. Tran +1
While Multiple Instance (MI) data are point patterns -- sets or multi-sets of unordered points -- appropriate statistical point pattern models have not been used in MI learning. Th…
Stabilizing Linear Prediction Models using Autoencoder
Shivapratap Gopakumar, Truyen Tran, Dinh Phung +1
To date, the instability of prognostic predictors in a sparse high dimensional model, which hinders their clinical adoption, has received little attention. Stable prediction is oft…