WuJie Wen

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Florida International University

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University of Connecticut

Assistant Professor, Department of Electrical and Computer Engineering at Florida International University

Featured Co-authors

Chang Liu
163 publications
Jie Xu
126 publications
Liang Zhao
111 publications
Jian Tang
110 publications
Xiang Chen
106 publications
Yanzhi Wang
103 publications
Qi Liu
100 publications
Xiao Wang
100 publications
Sijia Liu
87 publications
Yiran Chen
83 publications
Yiyu Shi
66 publications

research

∙ 06/11/2022

NeuGuard: Lightweight Neuron-Guided Defense against Membership Inference Attacks

Membership inference attacks (MIAs) against machine learning models can ...

Nuo Xu, et al. ∙

research

∙ 11/04/2020

Do Noises Bother Human and Neural Networks In the Same Way? A Medical Image Analysis Perspective

Deep learning had already demonstrated its power in medical images, incl...

Shao-Cheng Wen, et al. ∙

research

∙ 08/27/2019

Tiny but Accurate: A Pruned, Quantized and Optimized Memristor Crossbar Framework for Ultra Efficient DNN Implementation

The state-of-art DNN structures involve intensive computation and high m...

Xiaolong Ma, et al. ∙

research

∙ 06/13/2019

Thread Batching for High-performance Energy-efficient GPU Memory Design

Massive multi-threading in GPU imposes tremendous pressure on memory sub...

Bing Li, et al. ∙

research

∙ 04/09/2019

Machine Vision Guided 3D Medical Image Compression for Efficient Transmission and Accurate Segmentation in the Clouds

Cloud based medical image analysis has become popular recently due to th...

Zihao Liu, et al. ∙

research

∙ 03/23/2019

Progressive DNN Compression: A Key to Achieve Ultra-High Weight Pruning and Quantization Rates using ADMM

Weight pruning and weight quantization are two important categories of D...

Shaokai Ye, et al. ∙

research

∙ 12/12/2018

E-RNN: Design Optimization for Efficient Recurrent Neural Networks in FPGAs

Recurrent Neural Networks (RNNs) are becoming increasingly important for...

Zhe Li, et al. ∙

research

∙ 09/13/2018

Defensive Dropout for Hardening Deep Neural Networks under Adversarial Attacks

Deep neural networks (DNNs) are known vulnerable to adversarial attacks....

Siyue Wang, et al. ∙

research

∙ 07/29/2018

ADAM-ADMM: A Unified, Systematic Framework of Structured Weight Pruning for DNNs

Weight pruning methods of deep neural networks (DNNs) have been demonstr...

Tianyun Zhang, et al. ∙

research

∙ 04/10/2018

A Systematic DNN Weight Pruning Framework using Alternating Direction Method of Multipliers

Weight pruning methods for deep neural networks (DNNs) have been investi...

Tianyun Zhang, et al. ∙

research

∙ 03/14/2018

On the Universal Approximation Property and Equivalence of Stochastic Computing-based Neural Networks and Binary Neural Networks

Large-scale deep neural networks are both memory intensive and computati...

Yanzhi Wang, et al. ∙

research

∙ 03/14/2018

MT-Spike: A Multilayer Time-based Spiking Neuromorphic Architecture with Temporal Error Backpropagation

Modern deep learning enabled artificial neural networks, such as Deep Ne...

Tao Liu, et al. ∙

research

∙ 03/14/2018

PT-Spike: A Precise-Time-Dependent Single Spike Neuromorphic Architecture with Efficient Supervised Learning

One of the most exciting advancements in AI over the last decade is the ...

Tao Liu, et al. ∙

research

∙ 03/14/2018

Feature Distillation: DNN-Oriented JPEG Compression Against Adversarial Examples

Deep Neural Networks (DNNs) have achieved remarkable performance in a my...

Zihao Liu, et al. ∙

research

∙ 03/14/2018

DeepN-JPEG: A Deep Neural Network Favorable JPEG-based Image Compression Framework

As one of most fascinating machine learning techniques, deep neural netw...

Zihao Liu, et al. ∙

research

∙ 02/14/2018

Security Analysis and Enhancement of Model Compressed Deep Learning Systems under Adversarial Attacks

DNN is presenting human-level performance for many complex intelligent t...

Qi Liu, et al. ∙

research

∙ 05/09/2016

2.4GHZ Class AB power Amplifier For Healthcare Application

The objective of this research was to design a 2.4 GHz class AB Power Am...

Wei Cai, et al. ∙