Yiran Chen

is this you? claim profile

∙ 0 followers
Duke University ∙ Facebook ∙ University of Pittsburgh

Associate Professor, Co-director of Duke Center for Evolutionary Intelligence at Duke University since 2017, Associate Professor, Bicentennial Alumni Faculty Fellow at University of Pittsburgh since 2014, Assistant Professor at University of Pittsburgh from 2010-2014, Staff Engineer at Seagate LLC from 2007-2010, Sr. R&D Engineer I at Synopsys from 2005-2007, Research Assistant at Purdue University from 2001-2005, Intern Engineer at Micron Technology 2003, Intern Engineer at Micron Technology 2002, Ph.D. Electrical and Computer Engineering at Purdue University 2001-2005.

Featured Co-authors

Lawrence Carin
144 publications
Xin Liu
69 publications
Ang Li
60 publications
Xipeng Qiu
60 publications
Xuanjing Huang
56 publications
Xin Chen
54 publications
Bo Chen
41 publications
Fang Liu
40 publications
Hai Li
39 publications
Weiyao Lin
38 publications
Shuai Zhang
38 publications

LotteryFL: Personalized and Communication-Efficient Federated Learning with Lottery Ticket Hypothesis on Non-IID Datasets

Federated learning is a popular distributed machine learning paradigm wi...
08/07/2020 ∙ by Ang Li, et al. ∙ 0 ∙ share

read it
SparseTrain: Exploiting Dataflow Sparsity for Efficient Convolutional Neural Networks Training

Training Convolutional Neural Networks (CNNs) usually requires a large n...
07/21/2020 ∙ by Pengcheng Dai, et al. ∙ 0 ∙ share

read it
NASGEM: Neural Architecture Search via Graph Embedding Method

Neural Architecture Search (NAS) automates and prospers the design of ne...
07/08/2020 ∙ by Hsin-Pai Cheng, et al. ∙ 0 ∙ share

read it
Defending against GAN-based Deepfake Attacks via Transformation-aware Adversarial Faces

Deepfake represents a category of face-swapping attacks that leverage ma...
06/12/2020 ∙ by Chaofei Yang, et al. ∙ 0 ∙ share

read it
MVStylizer: An Efficient Edge-Assisted Video Photorealistic Style Transfer System for Mobile Phones

Recent research has made great progress in realizing neural style transf...
05/24/2020 ∙ by Ang Li, et al. ∙ 3 ∙ share

read it
TIPRDC: Task-Independent Privacy-Respecting Data Crowdsourcing Framework with Anonymized Intermediate Representations

The success of deep learning partially benefits from the availability of...
05/23/2020 ∙ by Ang Li, et al. ∙ 3 ∙ share

read it
PENNI: Pruned Kernel Sharing for Efficient CNN Inference

Although state-of-the-art (SOTA) CNNs achieve outstanding performance on...
05/14/2020 ∙ by Shiyu Li, et al. ∙ 0 ∙ share

read it
TRP: Trained Rank Pruning for Efficient Deep Neural Networks

To enable DNNs on edge devices like mobile phones, low-rank approximatio...
04/30/2020 ∙ by Yuhui Xu, et al. ∙ 8 ∙ share

read it
Perturbing Across the Feature Hierarchy to Improve Standard and Strict Blackbox Attack Transferability

We consider the blackbox transfer-based targeted adversarial attack thre...
04/29/2020 ∙ by Nathan Inkawhich, et al. ∙ 0 ∙ share

read it
Transferable Perturbations of Deep Feature Distributions

Almost all current adversarial attacks of CNN classifiers rely on inform...
04/27/2020 ∙ by Nathan Inkawhich, et al. ∙ 0 ∙ share

read it
Learning Low-rank Deep Neural Networks via Singular Vector Orthogonality Regularization and Singular Value Sparsification

Modern deep neural networks (DNNs) often require high memory consumption...
04/20/2020 ∙ by Huanrui Yang, et al. ∙ 10 ∙ share

read it
Extractive Summarization as Text Matching

This paper creates a paradigm shift with regard to the way we build neur...
04/19/2020 ∙ by Ming Zhong, et al. ∙ 0 ∙ share

read it
Neural Predictor for Neural Architecture Search

Neural Architecture Search methods are effective but often use complex a...
12/02/2019 ∙ by Wei Wen, et al. ∙ 0 ∙ share

read it
AutoShrink: A Topology-aware NAS for Discovering Efficient Neural Architecture

Resource is an important constraint when deploying Deep Neural Networks ...
11/21/2019 ∙ by Tunhou Zhang, et al. ∙ 0 ∙ share

read it
Structural sparsification for Far-field Speaker Recognition with GNA

Recently, deep neural networks (DNN) have been widely used in speaker re...
10/25/2019 ∙ by Jingchi Zhang, et al. ∙ 0 ∙ share

read it
Traned Rank Pruning for Efficient Deep Neural Networks

To accelerate DNNs inference, low-rank approximation has been widely ado...
10/09/2019 ∙ by Yuhui Xu, et al. ∙ 0 ∙ share

read it
Conditional Transferring Features: Scaling GANs to Thousands of Classes with 30

Generative adversarial network (GAN) has greatly improved the quality of...
09/25/2019 ∙ by Chunpeng Wu, et al. ∙ 0 ∙ share

read it
Towards Efficient and Secure Delivery of Data for Deep Learning with Privacy-Preserving

Privacy recently emerges as a severe concern in deep learning, that is, ...
09/17/2019 ∙ by Juncheng Shen, et al. ∙ 0 ∙ share

read it
DeepObfuscator: Adversarial Training Framework for Privacy-Preserving Image Classification

Deep learning has been widely utilized in many computer vision applicati...
09/09/2019 ∙ by Ang Li, et al. ∙ 21 ∙ share

read it
Accelerating CNN Training by Sparsifying Activation Gradients

Gradients to activations get involved in most of the calculations during...
08/01/2019 ∙ by Xucheng Ye, et al. ∙ 1 ∙ share

read it
RED: A ReRAM-based Deconvolution Accelerator

Deconvolution has been widespread in neural networks. For example, it is...
07/05/2019 ∙ by Zichen Fan, et al. ∙ 0 ∙ share

read it
SwiftNet: Using Graph Propagation as Meta-knowledge to Search Highly Representative Neural Architectures

Designing neural architectures for edge devices is subject to constraint...
06/19/2019 ∙ by Hsin-Pai, et al. ∙ 0 ∙ share

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

Massive multi-threading in GPU imposes tremendous pressure on memory sub...
06/13/2019 ∙ by Bing Li, et al. ∙ 0 ∙ share

read it
eSLAM: An Energy-Efficient Accelerator for Real-Time ORB-SLAM on FPGA Platform

Simultaneous Localization and Mapping (SLAM) is a critical task for auto...
06/03/2019 ∙ by Runze Liu, et al. ∙ 0 ∙ share

read it
Snooping Attacks on Deep Reinforcement Learning

Adversarial attacks have exposed a significant security vulnerability in...
05/28/2019 ∙ by Matthew Inkawhich, et al. ∙ 0 ∙ share

read it
Low-Power Computer Vision: Status, Challenges, Opportunities

Computer vision has achieved impressive progress in recent years. Meanwh...
04/15/2019 ∙ by Sergei Alyamkin, et al. ∙ 16 ∙ share

read it
Low Power Inference for On-Device Visual Recognition with a Quantization-Friendly Solution

The IEEE Low-Power Image Recognition Challenge (LPIRC) is an annual comp...
03/12/2019 ∙ by Chen Feng, et al. ∙ 6 ∙ share

read it
SPINBIS: Spintronics based Bayesian Inference System with Stochastic Computing

Bayesian inference is an effective approach for solving statistical lear...
02/19/2019 ∙ by Xiaotao Jia, et al. ∙ 0 ∙ share

read it
HyPar: Towards Hybrid Parallelism for Deep Learning Accelerator Array

With the rise of artificial intelligence in recent years, Deep Neural Ne...
01/07/2019 ∙ by Linghao Song, et al. ∙ 0 ∙ share

read it
Towards Leveraging the Information of Gradients in Optimization-based Adversarial Attack

In recent years, deep neural networks demonstrated state-of-the-art perf...
12/06/2018 ∙ by Jingyang Zhang, et al. ∙ 0 ∙ share

read it
Trained Rank Pruning for Efficient Deep Neural Networks

The performance of Deep Neural Networks (DNNs) keeps elevating in recent...
12/06/2018 ∙ by Yuhui Xu, et al. ∙ 0 ∙ share

read it
Adversarial Attacks for Optical Flow-Based Action Recognition Classifiers

The success of deep learning research has catapulted deep models into pr...
11/28/2018 ∙ by Nathan Inkawhich, et al. ∙ 0 ∙ share

read it
LEASGD: an Efficient and Privacy-Preserving Decentralized Algorithm for Distributed Learning

Distributed learning systems have enabled training large-scale models ov...
11/27/2018 ∙ by Hsin-Pai Cheng, et al. ∙ 0 ∙ share

read it
A Scalable Pipelined Dataflow Accelerator for Object Region Proposals on FPGA Platform

Region proposal is critical for object detection while it usually poses ...
10/26/2018 ∙ by Wenzhi Fu, et al. ∙ 0 ∙ share

read it
Differentiable Fine-grained Quantization for Deep Neural Network Compression

Neural networks have shown great performance in cognitive tasks. When de...
10/20/2018 ∙ by Hsin-Pai Cheng, et al. ∙ 0 ∙ share

read it
Generalized Inverse Optimization through Online Learning

Inverse optimization is a powerful paradigm for learning preferences and...
10/03/2018 ∙ by Chaosheng Dong, et al. ∙ 0 ∙ share

read it
2018 Low-Power Image Recognition Challenge

The Low-Power Image Recognition Challenge (LPIRC, https://rebootingcompu...
10/03/2018 ∙ by Sergei Alyamkin, et al. ∙ 6 ∙ share

read it
Morphed Learning: Towards Privacy-Preserving for Deep Learning Based Applications

The concern of potential privacy violation has prevented efficient use o...
09/20/2018 ∙ by Juncheng Shen, et al. ∙ 0 ∙ share

read it
2PFPCE: Two-Phase Filter Pruning Based on Conditional Entropy

Deep Convolutional Neural Networks (CNNs) offer remarkable performance o...
09/06/2018 ∙ by Chuhan Min, et al. ∙ 0 ∙ share

read it
AdvDetPatch: Attacking Object Detectors with Adversarial Patches

Object detectors have witnessed great progress in recent years and have ...
06/05/2018 ∙ by Xin Liu, et al. ∙ 2 ∙ share

read it
DPatch: Attacking Object Detectors with Adversarial Patches

Object detectors have witnessed great progress in recent years and have ...
06/05/2018 ∙ by Xin Liu, et al. ∙ 0 ∙ share

read it
SmoothOut: Smoothing Out Sharp Minima for Generalization in Large-Batch Deep Learning

In distributed deep learning, a large batch size in Stochastic Gradient ...
05/21/2018 ∙ by Wei Wen, et al. ∙ 0 ∙ share

read it
Exploiting Spin-Orbit Torque Devices as Reconfigurable Logic for Circuit Obfuscation

Circuit obfuscation is a frequently used approach to conceal logic funct...
02/08/2018 ∙ by Jianlei Yang, et al. ∙ 0 ∙ share

read it
Spintronics based Stochastic Computing for Efficient Bayesian Inference System

Bayesian inference is an effective approach for solving statistical lear...
11/03/2017 ∙ by Xiaotao Jia, et al. ∙ 0 ∙ share

read it
Learning Intrinsic Sparse Structures within Long Short-Term Memory

Model compression is significant for the wide adoption of Recurrent Neur...
09/15/2017 ∙ by Wei Wen, et al. ∙ 0 ∙ share

read it
GraphR: Accelerating Graph Processing Using ReRAM

This paper presents GRAPHR, the first ReRAM-based graph processing accel...
08/21/2017 ∙ by Linghao Song, et al. ∙ 0 ∙ share

read it
A Multi-strength Adversarial Training Method to Mitigate Adversarial Attacks

Some recent works revealed that deep neural networks (DNNs) are vulnerab...
05/27/2017 ∙ by Chang Song, et al. ∙ 0 ∙ share

read it
TernGrad: Ternary Gradients to Reduce Communication in Distributed Deep Learning

High network communication cost for synchronizing gradients and paramete...
05/22/2017 ∙ by Wei Wen, et al. ∙ 0 ∙ share

read it
Coordinating Filters for Faster Deep Neural Networks

Very large-scale Deep Neural Networks (DNNs) have achieved remarkable su...
03/28/2017 ∙ by Wei Wen, et al. ∙ 0 ∙ share

read it
A Compact DNN: Approaching GoogLeNet-Level Accuracy of Classification and Domain Adaptation

Recently, DNN model compression based on network architecture design, e....
03/12/2017 ∙ by Chunpeng Wu, et al. ∙ 0 ∙ share

read it