activity
20182023
most citedSkyNet: a Hardware-Efficient Method for Object Detection and Tracking on Embedded Systems

83 citations · 734 across the 57 of their papers we have counts for

collaborators
Showing 2020Show all

20 papers · 1 filter

quant-ph2020★ 25 cited

When Machine Learning Meets Quantum Computers: A Case Study

Weiwen Jiang, Jinjun Xiong, Yiyu Shi

Along with the development of AI democratization, the machine learning approach, in particular neural networks, has been applied to wide-range applications. In different applicatio…

cs.DC2020★ 1 cited

TEMPI: An Interposed MPI Library with a Canonical Representation of CUDA-aware Datatypes

Carl Pearson, Kun Wu, I-Hsin Chung +2

MPI derived datatypes are an abstraction that simplifies handling of non-contiguous data in MPI applications. These datatypes are recursively constructed at runtime from primitive…

cs.NI2020★ 3 cited

Efficient Neural Network Implementation with Quadratic Neuron

Zirui Xu, Jinjun Xiong, Fuxun Yu +1

Previous works proved that the combination of the linear neuron network with nonlinear activation functions (e.g. ReLu) can achieve nonlinear function approximation. However, simpl…

cs.CV2020★ 2 cited

Interpretable Visual Reasoning via Induced Symbolic Space

Zhonghao Wang, Kai Wang, Mo Yu +4

We study the problem of concept induction in visual reasoning, i.e., identifying concepts and their hierarchical relationships from question-answer pairs associated with images; an…

cs.AR2020

Effective Algorithm-Accelerator Co-design for AI Solutions on Edge Devices

Cong Hao, Yao Chen, Xiaofan Zhang +4

High quality AI solutions require joint optimization of AI algorithms, such as deep neural networks (DNNs), and their hardware accelerators. To improve the overall solution quality…

cs.CL2020

Exploring Semantic Capacity of Terms

Jie Huang, Zilong Wang, Kevin Chen-Chuan Chang +2

We introduce and study semantic capacity of terms. For example, the semantic capacity of artificial intelligence is higher than that of linear regression since artificial intellige…

cs.AR2020★ 6 cited

Tearing Down the Memory Wall

Zaid Qureshi, Vikram Sharma Mailthody, Seung Won Min +3

We present a vision for the Erudite architecture that redefines the compute and memory abstractions such that memory bandwidth and capacity become first-class citizens along with c…

cs.AR2020★ 15 cited

DNNExplorer: A Framework for Modeling and Exploring a Novel Paradigm of FPGA-based DNN Accelerator

Xiaofan Zhang, Hanchen Ye, Junsong Wang +4

Existing FPGA-based DNN accelerators typically fall into two design paradigms. Either they adopt a generic reusable architecture to support different DNN networks but leave some pe…

cs.LG2020★ 20 cited

Practical Detection of Trojan Neural Networks: Data-Limited and Data-Free Cases

Ren Wang, Gaoyuan Zhang, Sijia Liu +3

When the training data are maliciously tampered, the predictions of the acquired deep neural network (DNN) can be manipulated by an adversary known as the Trojan attack (or poisoni…

eess.IV2020

ICA-UNet: ICA Inspired Statistical UNet for Real-time 3D Cardiac Cine MRI Segmentation

Tianchen Wang, Xiaowei Xu, Jinjun Xiong +5

Real-time cine magnetic resonance imaging (MRI) plays an increasingly important role in various cardiac interventions. In order to enable fast and accurate visual assistance, the t…

cs.DC2020

At-Scale Sparse Deep Neural Network Inference with Efficient GPU Implementation

Mert Hidayetoglu, Carl Pearson, Vikram Sharma Mailthody +4

This paper presents GPU performance optimization and scaling results for inference models of the Sparse Deep Neural Network Challenge 2020. Demands for network quality have increas…

quant-ph2020★ 53 cited

A Co-Design Framework of Neural Networks and Quantum Circuits Towards Quantum Advantage

Weiwen Jiang, Jinjun Xiong, Yiyu Shi

Despite the pursuit of quantum advantages in various applications, the power of quantum computers in neural network computations has mostly remained unknown, primarily due to a mis…

cs.DC2020★ 10 cited

EMOGI: Efficient Memory-access for Out-of-memory Graph-traversal In GPUs

Seung Won Min, Vikram Sharma Mailthody, Zaid Qureshi +3

Modern analytics and recommendation systems are increasingly based on graph data that capture the relations between entities being analyzed. Practical graphs come in huge sizes, of…

cs.SE2020★ 51 cited

A Multi-Perspective Architecture for Semantic Code Search

Rajarshi Haldar, Lingfei Wu, Jinjun Xiong +1

The ability to match pieces of code to their corresponding natural language descriptions and vice versa is fundamental for natural language search interfaces to software repositori…

cs.LG2020★ 9 cited

EDD: Efficient Differentiable DNN Architecture and Implementation Co-search for Embedded AI Solutions

Yuhong Li, Cong Hao, Xiaofan Zhang +5

High quality AI solutions require joint optimization of AI algorithms and their hardware implementations. In this work, we are the first to propose a fully simultaneous, efficient…

cs.CV2020★ 2 cited

Alleviating Semantic-level Shift: A Semi-supervised Domain Adaptation Method for Semantic Segmentation

Zhonghao Wang, Yunchao Wei, Rogerior Feris +4

Learning segmentation from synthetic data and adapting to real data can significantly relieve human efforts in labelling pixel-level masks. A key challenge of this task is how to a…

cs.CV2020★ 19 cited

Differential Treatment for Stuff and Things: A Simple Unsupervised Domain Adaptation Method for Semantic Segmentation

Zhonghao Wang, Mo Yu, Yunchao Wei +5

We consider the problem of unsupervised domain adaptation for semantic segmentation by easing the domain shift between the source domain (synthetic data) and the target domain (rea…

eess.IV2020

Multi-Cycle-Consistent Adversarial Networks for CT Image Denoising

Jinglan Liu, Yukun Ding, Jinjun Xiong +6

CT image denoising can be treated as an image-to-image translation task where the goal is to learn the transform between a source domain (noisy images) and a target domain …

cs.LG2020★ 2 cited

DLSpec: A Deep Learning Task Exchange Specification

Abdul Dakkak, Cheng Li, Jinjun Xiong +1

Deep Learning (DL) innovations are being introduced at a rapid pace. However, the current lack of standard specification of DL tasks makes sharing, running, reproducing, and compar…

cs.DC2020★ 5 cited

MLModelScope: A Distributed Platform for Model Evaluation and Benchmarking at Scale

Abdul Dakkak, Cheng Li, Jinjun Xiong +1

Machine Learning (ML) and Deep Learning (DL) innovations are being introduced at such a rapid pace that researchers are hard-pressed to analyze and study them. The complicated proc…