Jun Han

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Swinburne University of Technology ∙ Dartmouth College ∙ National University of Singapore

Disentangled Recurrent Wasserstein Autoencoder

Learning disentangled representations leads to interpretable models and ...
01/19/2021 ∙ by Jun Han, et al. ∙ 12 ∙ share

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Heuristic-based Mining of Service Behavioral Models from Interaction Traces

Software behavioral models have proven useful for emulating and testing ...
11/01/2020 ∙ by Muhammad Ashad Kabir, et al. ∙ 0 ∙ share

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p-order Tensor Products with Invertible Linear Transforms

This paper studies the issues about tensors. Three typical kinds of tens...
05/23/2020 ∙ by Jun Han, et al. ∙ 0 ∙ share

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LaNet: Real-time Lane Identification by Learning Road SurfaceCharacteristics from Accelerometer Data

The resolution of GPS measurements, especially in urban areas, is insuff...
04/06/2020 ∙ by Madhumitha Harishankar, et al. ∙ 0 ∙ share

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Scalable Approximate Inference and Some Applications

Approximate inference in probability models is a fundamental task in mac...
03/07/2020 ∙ by Jun Han, et al. ∙ 0 ∙ share

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Stein Variational Inference for Discrete Distributions

Gradient-based approximate inference methods, such as Stein variational ...
03/01/2020 ∙ by Jun Han, et al. ∙ 15 ∙ share

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SDSN@RT: a middleware environment for single-instance multi-tenant cloud applications

With the Single-Instance Multi-Tenancy (SIMT) model for composite Softwa...
02/10/2020 ∙ by Indika Kumara, et al. ∙ 0 ∙ share

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FM4SN: A Feature-Oriented Approach to Tenant-Driven Customization of Multi-Tenant Service Networks

In a multi-tenant service network, multiple virtual service networks (VS...
02/10/2020 ∙ by Indika Kumara, et al. ∙ 0 ∙ share

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CalBehav: A Machine Learning based Personalized Calendar Behavioral Model using Time-Series Smartphone Data

The electronic calendar is a valuable resource nowadays for managing our...
09/02/2019 ∙ by Iqbal H. Sarker, et al. ∙ 0 ∙ share

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LINS: A Lidar-Inerital State Estimator for Robust and Fast Navigation

Robust and fast ego-motion estimation is a critical problem for autonomo...
07/04/2019 ∙ by Chao Qin, et al. ∙ 0 ∙ share

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SurFi: Detecting Surveillance Camera Looping Attacks with Wi-Fi Channel State Information (Extended Version)

The proliferation of surveillance cameras has greatly improved the physi...
04/02/2019 ∙ by Nitya Lakshmanan, et al. ∙ 0 ∙ share

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ContextServ: Towards Model-Driven Development of Context-AwareWeb Services

In the era of Web of Things and Services, Context-aware Web Services (CA...
11/30/2018 ∙ by Quan Z. Sheng, et al. ∙ 0 ∙ share

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Individualized Time-Series Segmentation for Mining Mobile Phone User Behavior

Mobile phones can record individual's daily behavioral data as a time-se...
11/15/2018 ∙ by Iqbal H. Sarker, et al. ∙ 0 ∙ share

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Deep Probabilistic Video Compression

We propose a variational inference approach to deep probabilistic video ...
10/05/2018 ∙ by Jun Han, et al. ∙ 0 ∙ share

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Stein Variational Gradient Descent Without Gradient

Stein variational gradient decent (SVGD) has been shown to be a powerful...
06/07/2018 ∙ by Jun Han, et al. ∙ 0 ∙ share

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A hybrid architecture for astronomical computing

With many large science equipment constructing and putting into use, ast...
01/19/2018 ∙ by Changhua Li, et al. ∙ 0 ∙ share

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Identifying Recent Behavioral Data Length in Mobile Phone Log

Mobile phone log data (e.g., phone call log) is not static as it is prog...
11/18/2017 ∙ by Iqbal H. Sarker, et al. ∙ 0 ∙ share

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An Improved Naive Bayes Classifier-based Noise Detection Technique for Classifying User Phone Call Behavior

The presence of noisy instances in mobile phone data is a fundamental is...
10/12/2017 ∙ by Iqbal H. Sarker, et al. ∙ 0 ∙ share

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Stein Variational Adaptive Importance Sampling

We propose a novel adaptive importance sampling algorithm which incorpor...
04/18/2017 ∙ by Jun Han, et al. ∙ 0 ∙ share

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Bootstrap Model Aggregation for Distributed Statistical Learning

In distributed, or privacy-preserving learning, we are often given a set...
07/04/2016 ∙ by Jun Han, et al. ∙ 0 ∙ share

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Jun Han

Featured Co-authors

Qiang Liu

Ming Liu

Jian Peng

Lorenzo Torresani

Liang Liu

Xiao Chen

Stephan Mandt

Xianglong Liu

Xuan Zhang

Quan Z. Sheng

Martin Renqiang Min

Disentangled Recurrent Wasserstein Autoencoder

Heuristic-based Mining of Service Behavioral Models from Interaction Traces

p-order Tensor Products with Invertible Linear Transforms

LaNet: Real-time Lane Identification by Learning Road SurfaceCharacteristics from Accelerometer Data

Scalable Approximate Inference and Some Applications

Stein Variational Inference for Discrete Distributions

SDSN@RT: a middleware environment for single-instance multi-tenant cloud applications

FM4SN: A Feature-Oriented Approach to Tenant-Driven Customization of Multi-Tenant Service Networks

CalBehav: A Machine Learning based Personalized Calendar Behavioral Model using Time-Series Smartphone Data

LINS: A Lidar-Inerital State Estimator for Robust and Fast Navigation

SurFi: Detecting Surveillance Camera Looping Attacks with Wi-Fi Channel State Information (Extended Version)

ContextServ: Towards Model-Driven Development of Context-AwareWeb Services

Individualized Time-Series Segmentation for Mining Mobile Phone User Behavior

Deep Probabilistic Video Compression

Stein Variational Gradient Descent Without Gradient

A hybrid architecture for astronomical computing

Identifying Recent Behavioral Data Length in Mobile Phone Log

An Improved Naive Bayes Classifier-based Noise Detection Technique for Classifying User Phone Call Behavior

Stein Variational Adaptive Importance Sampling

Bootstrap Model Aggregation for Distributed Statistical Learning