Svetha Venkatesh

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Deakin University ∙ Curtin University

Australian Laureate Fellow Alfred Deakin Professor and Director Center for Pattern Recognition and Data Analytics (PRaDA) at Deakin University

HyperVAE: A Minimum Description Length Variational Hyper-Encoding Network

We propose a framework called HyperVAE for encoding distributions of dis...
05/18/2020 ∙ by Phuoc Nguyen, et al. ∙ 56 ∙ share

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Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detection

Deep autoencoder has been extensively used for anomaly detection. Traini...
04/04/2019 ∙ by Dong Gong, et al. ∙ 34 ∙ share

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Improving Generalization and Stability of Generative Adversarial Networks

Generative Adversarial Networks (GANs) are one of the most popular tools...
02/11/2019 ∙ by Hoang Thanh-Tung, et al. ∙ 26 ∙ share

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Distributionally Robust Bayesian Quadrature Optimization

Bayesian quadrature optimization (BQO) maximizes the expectation of an e...
01/19/2020 ∙ by Thanh Tang Nguyen, et al. ∙ 23 ∙ share

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Learning Transferable Domain Priors for Safe Exploration in Reinforcement Learning

Prior access to domain knowledge could significantly improve the perform...
09/10/2019 ∙ by Thommen George Karimpanal, et al. ∙ 13 ∙ share

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Self-Assttentive Associative Memory

Heretofore, neural networks with external memory are restricted to singl...
02/10/2020 ∙ by Hung Le, et al. ∙ 13 ∙ share

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Bayesian Optimization for Categorical and Category-Specific Continuous Inputs

Many real-world functions are defined over both categorical and category...
11/28/2019 ∙ by Dang Nguyen, et al. ∙ 12 ∙ share

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Self-Attentive Associative Memory

Heretofore, neural networks with external memory are restricted to singl...
02/10/2020 ∙ by Hung Le, et al. ∙ 12 ∙ share

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Bayesian functional optimisation with shape prior

Real world experiments are expensive, and thus it is important to reach ...
09/19/2018 ∙ by Pratibha Vellanki, et al. ∙ 8 ∙ share

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Learning Regularity in Skeleton Trajectories for Anomaly Detection in Videos

Appearance features have been widely used in video anomaly detection eve...
03/08/2019 ∙ by Romero Morais, et al. ∙ 6 ∙ share

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Graph Transformation Policy Network for Chemical Reaction Prediction

We address a fundamental problem in chemistry known as chemical reaction...
12/22/2018 ∙ by Kien Do, et al. ∙ 6 ∙ share

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Hierarchical Conditional Relation Networks for Video Question Answering

Video question answering (VideoQA) is challenging as it requires modelin...
02/25/2020 ∙ by Thao Minh Le, et al. ∙ 6 ∙ share

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Dynamic Language Binding in Relational Visual Reasoning

We present Language-binding Object Graph Network, the first neural reaso...
04/30/2020 ∙ by Thao Minh Le, et al. ∙ 6 ∙ share

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Learning to Remember More with Less Memorization

Memory-augmented neural networks consisting of a neural controller and a...
01/05/2019 ∙ by Hung Le, et al. ∙ 4 ∙ share

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Learning to Reason with Relational Video Representation for Question Answering

How does machine learn to reason about the content of a video in answeri...
07/10/2019 ∙ by Thao Minh Le, et al. ∙ 4 ∙ share

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Incorporating Expert Prior Knowledge into Experimental Design via Posterior Sampling

Scientific experiments are usually expensive due to complex experimental...
02/26/2020 ∙ by Cheng Li, et al. ∙ 4 ∙ share

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Incorporating Expert Prior in Bayesian Optimisation via Space Warping

Bayesian optimisation is a well-known sample-efficient method for the op...
03/27/2020 ∙ by Anil Ramachandran, et al. ∙ 3 ∙ share

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On catastrophic forgetting and mode collapse in Generative Adversarial Networks

Generative Adversarial Networks (GAN) are one of the most prominent tool...
07/11/2018 ∙ by Hoang Thanh-Tung, et al. ∙ 2 ∙ share

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Statistical Latent Space Approach for Mixed Data Modelling and Applications

The analysis of mixed data has been raising challenges in statistics and...
08/18/2017 ∙ by Tu Dinh Nguyen, et al. ∙ 0 ∙ share

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Graph Classification via Deep Learning with Virtual Nodes

Learning representation for graph classification turns a variable-size g...
08/14/2017 ∙ by Trang Pham, et al. ∙ 0 ∙ share

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Deep Learning to Attend to Risk in ICU

Modeling physiological time-series in ICU is of high clinical importance...
07/17/2017 ∙ by Phuoc Nguyen, et al. ∙ 0 ∙ share

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One Size Fits Many: Column Bundle for Multi-X Learning

Much recent machine learning research has been directed towards leveragi...
02/22/2017 ∙ by Trang Pham, et al. ∙ 0 ∙ share

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Stabilizing Linear Prediction Models using Autoencoder

To date, the instability of prognostic predictors in a sparse high dimen...
09/28/2016 ∙ by Shivapratap Gopakumar, et al. ∙ 0 ∙ share

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Column Networks for Collective Classification

Relational learning deals with data that are characterized by relational...
09/15/2016 ∙ by Trang Pham, et al. ∙ 0 ∙ share

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Outlier Detection on Mixed-Type Data: An Energy-based Approach

Outlier detection amounts to finding data points that differ significant...
08/17/2016 ∙ by Kien Do, et al. ∙ 0 ∙ share

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Faster Training of Very Deep Networks Via p-Norm Gates

A major contributing factor to the recent advances in deep neural networ...
08/11/2016 ∙ by Trang Pham, et al. ∙ 0 ∙ share

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Preterm Birth Prediction: Deriving Stable and Interpretable Rules from High Dimensional Data

Preterm births occur at an alarming rate of 10-15 risk of infant mortali...
07/28/2016 ∙ by Truyen Tran, et al. ∙ 0 ∙ share

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Deepr: A Convolutional Net for Medical Records

Feature engineering remains a major bottleneck when creating predictive ...
07/26/2016 ∙ by Phuoc Nguyen, et al. ∙ 0 ∙ share

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An evaluation of randomized machine learning methods for redundant data: Predicting short and medium-term suicide risk from administrative records and risk assessments

Accurate prediction of suicide risk in mental health patients remains an...
05/03/2016 ∙ by Thuong Nguyen, et al. ∙ 0 ∙ share

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Choice by Elimination via Deep Neural Networks

We introduce Neural Choice by Elimination, a new framework that integrat...
02/17/2016 ∙ by Truyen Tran, et al. ∙ 0 ∙ share

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Collaborative filtering via sparse Markov random fields

Recommender systems play a central role in providing individualized acce...
02/09/2016 ∙ by Truyen Tran, et al. ∙ 0 ∙ share

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DeepCare: A Deep Dynamic Memory Model for Predictive Medicine

Personalized predictive medicine necessitates the modeling of patient il...
02/01/2016 ∙ by Trang Pham, et al. ∙ 0 ∙ share

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Achieving stable subspace clustering by post-processing generic clustering results

We propose an effective subspace selection scheme as a post-processing s...
05/27/2016 ∙ by Duc-Son Pham, et al. ∙ 0 ∙ share

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Learning deep representation of multityped objects and tasks

We introduce a deep multitask architecture to integrate multityped repre...
03/04/2016 ∙ by Truyen Tran, et al. ∙ 0 ∙ share

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MCMC for Hierarchical Semi-Markov Conditional Random Fields

Deep architecture such as hierarchical semi-Markov models is an importan...
08/06/2014 ∙ by Truyen Tran, et al. ∙ 0 ∙ share

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Mixed-Variate Restricted Boltzmann Machines

Modern datasets are becoming heterogeneous. To this end, we present in t...
08/06/2014 ∙ by Truyen Tran, et al. ∙ 0 ∙ share

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Thurstonian Boltzmann Machines: Learning from Multiple Inequalities

We introduce Thurstonian Boltzmann Machines (TBM), a unified architectur...
08/01/2014 ∙ by Truyen Tran, et al. ∙ 0 ∙ share

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Cumulative Restricted Boltzmann Machines for Ordinal Matrix Data Analysis

Ordinal data is omnipresent in almost all multiuser-generated feedback -...
07/31/2014 ∙ by Truyen Tran, et al. ∙ 0 ∙ share

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Learning From Ordered Sets and Applications in Collaborative Ranking

Ranking over sets arise when users choose between groups of items. For e...
07/31/2014 ∙ by Truyen Tran, et al. ∙ 0 ∙ share

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Permutation Models for Collaborative Ranking

We study the problem of collaborative filtering where ranking informatio...
07/23/2014 ∙ by Truyen Tran, et al. ∙ 0 ∙ share

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Stabilizing Sparse Cox Model using Clinical Structures in Electronic Medical Records

Stability in clinical prediction models is crucial for transferability b...
07/23/2014 ∙ by Shivapratap Gopakumar, et al. ∙ 0 ∙ share

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Learning Rank Functionals: An Empirical Study

Ranking is a key aspect of many applications, such as information retrie...
07/23/2014 ∙ by Truyen Tran, et al. ∙ 0 ∙ share

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Bayesian Nonparametric Multilevel Clustering with Group-Level Contexts

We present a Bayesian nonparametric framework for multilevel clustering ...
01/09/2014 ∙ by Vu Nguyen, et al. ∙ 0 ∙ share

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The adaptable buffer algorithm for high quantile estimation in non-stationary data streams

The need to estimate a particular quantile of a distribution is an impor...
04/21/2015 ∙ by Ognjen Arandjelovic, et al. ∙ 0 ∙ share

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Groupwise registration of aerial images

This paper addresses the task of time separated aerial image registratio...
04/21/2015 ∙ by Ognjen Arandjelovic, et al. ∙ 0 ∙ share

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Viewpoint distortion compensation in practical surveillance systems

Our aim is to estimate the perspective-effected geometric distortion of ...
04/21/2015 ∙ by Ognjen Arandjelovic, et al. ∙ 0 ∙ share

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Efficient algorithms for robust recovery of images from compressed data

Compressed sensing (CS) is an important theory for sub-Nyquist sampling ...
11/26/2012 ∙ by Duc-Son Pham, et al. ∙ 0 ∙ share

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Boosted Markov Networks for Activity Recognition

We explore a framework called boosted Markov networks to combine the lea...
08/06/2014 ∙ by Truyen Tran, et al. ∙ 0 ∙ share

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Human Activity Learning and Segmentation using Partially Hidden Discriminative Models

Learning and understanding the typical patterns in the daily activities ...
08/06/2014 ∙ by Truyen Tran, et al. ∙ 0 ∙ share

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Learning Structured Outputs from Partial Labels using Forest Ensemble

Learning structured outputs with general structures is computationally c...
07/24/2014 ∙ by Truyen Tran, et al. ∙ 0 ∙ share

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Svetha Venkatesh

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