892 citations · 2.3k across the 60 of their papers we have counts for
8 papers · 2 filters
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…
Outlier Detection on Mixed-Type Data: An Energy-based Approach
Kien Do, Truyen Tran, Dinh Phung +1
Outlier detection amounts to finding data points that differ significantly from the norm. Classic outlier detection methods are largely designed for single data type such as contin…
Faster Training of Very Deep Networks Via p-Norm Gates
Trang Pham, Truyen Tran, Dinh Phung +1
A major contributing factor to the recent advances in deep neural networks is structural units that let sensory information and gradients to propagate easily. Gating is one such st…
An evaluation of randomized machine learning methods for redundant data: Predicting short and medium-term suicide risk from administrative records and risk assessments
Thuong Nguyen, Truyen Tran, Shivapratap Gopakumar +2
Accurate prediction of suicide risk in mental health patients remains an open problem. Existing methods including clinician judgments have acceptable sensitivity, but yield many fa…
Learning deep representation of multityped objects and tasks
Truyen Tran, Dinh Phung, Svetha Venkatesh
We introduce a deep multitask architecture to integrate multityped representations of multimodal objects. This multitype exposition is less abstract than the multimodal characteriz…
Choice by Elimination via Deep Neural Networks
Truyen Tran, Dinh Phung, Svetha Venkatesh
We introduce Neural Choice by Elimination, a new framework that integrates deep neural networks into probabilistic sequential choice models for learning to rank. Given a set of ite…