b'Jun Han'

research

∙ 04/13/2022

DL4SciVis: A State-of-the-Art Survey on Deep Learning for Scientific Visualization

Since 2016, we have witnessed the tremendous growth of artificial intell...

Chaoli Wang, et al. ∙

research

∙ 03/18/2022

Generative Principal Component Analysis

In this paper, we study the problem of principal component analysis with...

Zhaoqiang Liu, et al. ∙

research

∙ 09/28/2021

Touchtone leakage attacks via smartphone sensors: mitigation without hardware modification

Smartphone motion sensors provide a concealed mechanism for eavesdroppin...

Connor Bolton, et al. ∙

research

∙ 08/08/2021

Robust 1-bit Compressive Sensing with Partial Gaussian Circulant Matrices and Generative Priors

In 1-bit compressive sensing, each measurement is quantized to a single ...

Zhaoqiang Liu, et al. ∙

research

∙ 08/06/2021

TS4Net: Two-Stage Sample Selective Strategy for Rotating Object Detection

Rotating object detection has wide applications in aerial photographs, r...

Kai Feng, et al. ∙

research

∙ 07/10/2021

Hierarchical Self-Supervised Learning for Medical Image Segmentation Based on Multi-Domain Data Aggregation

A large labeled dataset is a key to the success of supervised deep learn...

Hao Zheng, et al. ∙

research

∙ 06/09/2021

FastZIP: Faster and More Secure Zero-Interaction Pairing

With the advent of the Internet of Things (IoT), establishing a secure c...

Mikhail Fomichev, et al. ∙

research

∙ 01/19/2021

Disentangled Recurrent Wasserstein Autoencoder

Learning disentangled representations leads to interpretable models and ...

Jun Han, et al. ∙

research

∙ 11/01/2020

Heuristic-based Mining of Service Behavioral Models from Interaction Traces

Software behavioral models have proven useful for emulating and testing ...

Muhammad Ashad Kabir, et al. ∙

research

∙ 05/23/2020

p-order Tensor Products with Invertible Linear Transforms

This paper studies the issues about tensors. Three typical kinds of tens...

Jun Han, et al. ∙

research

∙ 04/06/2020

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

The resolution of GPS measurements, especially in urban areas, is insuff...

Madhumitha Harishankar, et al. ∙

research

∙ 03/07/2020

Scalable Approximate Inference and Some Applications

Approximate inference in probability models is a fundamental task in mac...

Jun Han, et al. ∙

research

∙ 03/01/2020

Stein Variational Inference for Discrete Distributions

Gradient-based approximate inference methods, such as Stein variational ...

Jun Han, et al. ∙

research

∙ 02/10/2020

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

With the Single-Instance Multi-Tenancy (SIMT) model for composite Softwa...

Indika Kumara, et al. ∙

research

∙ 02/10/2020

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...

Indika Kumara, et al. ∙

research

∙ 09/02/2019

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...

Iqbal H. Sarker, et al. ∙

research

∙ 07/04/2019

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

Robust and fast ego-motion estimation is a critical problem for autonomo...

Chao Qin, et al. ∙

research

∙ 04/02/2019

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

The proliferation of surveillance cameras has greatly improved the physi...

Nitya Lakshmanan, et al. ∙

research

∙ 11/30/2018

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

In the era of Web of Things and Services, Context-aware Web Services (CA...

Quan Z. Sheng, et al. ∙

research

∙ 11/15/2018

Individualized Time-Series Segmentation for Mining Mobile Phone User Behavior

Mobile phones can record individual's daily behavioral data as a time-se...

Iqbal H. Sarker, et al. ∙

research

∙ 10/05/2018

Deep Probabilistic Video Compression

We propose a variational inference approach to deep probabilistic video ...

Jun Han, et al. ∙

research

∙ 06/07/2018

Stein Variational Gradient Descent Without Gradient

Stein variational gradient decent (SVGD) has been shown to be a powerful...

Jun Han, et al. ∙

research

∙ 01/19/2018

A hybrid architecture for astronomical computing

With many large science equipment constructing and putting into use, ast...

Changhua Li, et al. ∙

research

∙ 11/18/2017

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...

Iqbal H. Sarker, et al. ∙

research

∙ 10/12/2017

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...

Iqbal H. Sarker, et al. ∙

research

∙ 04/18/2017

Stein Variational Adaptive Importance Sampling

We propose a novel adaptive importance sampling algorithm which incorpor...

Jun Han, et al. ∙

research

∙ 07/04/2016

Bootstrap Model Aggregation for Distributed Statistical Learning

In distributed, or privacy-preserving learning, we are often given a set...

Jun Han, et al. ∙

Jun Han

Featured Co-authors

Qiang Liu

Ming Liu

Lin Yang

Jian Peng

Xiao Chen

Jonathan Scarlett

Lorenzo Torresani

Stephan Mandt

Matthias Hollick

Liang Liu

Xuan Zhang

DL4SciVis: A State-of-the-Art Survey on Deep Learning for Scientific Visualization

Generative Principal Component Analysis

Touchtone leakage attacks via smartphone sensors: mitigation without hardware modification

Robust 1-bit Compressive Sensing with Partial Gaussian Circulant Matrices and Generative Priors

TS4Net: Two-Stage Sample Selective Strategy for Rotating Object Detection

Hierarchical Self-Supervised Learning for Medical Image Segmentation Based on Multi-Domain Data Aggregation

FastZIP: Faster and More Secure Zero-Interaction Pairing

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