b'Jinjun Xiong'

research

∙ 12/28/2021

HiKonv: High Throughput Quantized Convolution With Novel Bit-wise Management and Computation

Quantization for Convolutional Neural Network (CNN) has shown significan...

Xinheng Liu, et al. ∙

research

∙ 11/10/2021

Graph Neural Network Training with Data Tiering

Graph Neural Networks (GNNs) have shown success in learning from graph-s...

Seung Won Min, et al. ∙

research

∙ 11/09/2021

MLHarness: A Scalable Benchmarking System for MLCommons

With the society's growing adoption of machine learning (ML) and deep le...

Yen-Hsiang Chang, et al. ∙

research

∙ 10/12/2021

Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Pruned Neural Networks

The lottery ticket hypothesis (LTH) states that learning on a properly p...

Shuai Zhang, et al. ∙

research

∙ 09/08/2021

Exploration of Quantum Neural Architecture by Mixing Quantum Neuron Designs

With the constant increase of the number of quantum bits (qubits) in the...

Zhepeng Wang, et al. ∙

research

∙ 09/08/2021

Can Noise on Qubits Be Learned in Quantum Neural Network? A Case Study on QuantumFlow

In the noisy intermediate-scale quantum (NISQ) era, one of the key quest...

Zhiding Liang, et al. ∙

research

∙ 08/20/2021

Open Relation Modeling: Learning to Define Relations between Entities

Relations between entities can be represented by different instances, e....

Jie Huang, et al. ∙

research

∙ 08/04/2021

Generic Neural Architecture Search via Regression

Most existing neural architecture search (NAS) algorithms are dedicated ...

Yuhong Li, et al. ∙

research

∙ 06/16/2021

Global Rhythm Style Transfer Without Text Transcriptions

Prosody plays an important role in characterizing the style of a speaker...

Kaizhi Qian, et al. ∙

research

∙ 05/27/2021

Measuring Fine-Grained Domain Relevance of Terms: A Hierarchical Core-Fringe Approach

We propose to measure fine-grained domain relevance - the degree that a ...

Jie Huang, et al. ∙

research

∙ 05/19/2021

Heterogeneous Contrastive Learning

With the advent of big data across multiple high-impact applications, we...

Lecheng Zheng, et al. ∙

research

∙ 04/27/2021

K-Clique Counting on GPUs

Counting k-cliques in a graph is an important problem in graph analysis ...

Mohammad Almasri, et al. ∙

research

∙ 03/25/2021

Enabling Design Methodologies and Future Trends for Edge AI: Specialization and Co-design

Artificial intelligence (AI) technologies have dramatically advanced in ...

Cong Hao, et al. ∙

research

∙ 03/04/2021

Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture

Graph Convolutional Networks (GCNs) are increasingly adopted in large-sc...

Seung Won Min, et al. ∙

research

∙ 01/20/2021

PyTorch-Direct: Enabling GPU Centric Data Access for Very Large Graph Neural Network Training with Irregular Accesses

With the increasing adoption of graph neural networks (GNNs) in the mach...

Seung Won Min, et al. ∙

research

∙ 01/19/2021

Safer Illinois and RokWall: Privacy Preserving University Health Apps for COVID-19

COVID-19 has fundamentally disrupted the way we live. Government bodies,...

Vikram Sharma Mailthody, et al. ∙

research

∙ 12/28/2020

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

MPI derived datatypes are an abstraction that simplifies handling of non...

Carl Pearson, et al. ∙

research

∙ 12/18/2020

When Machine Learning Meets Quantum Computers: A Case Study

Along with the development of AI democratization, the machine learning a...

Weiwen Jiang, et al. ∙

research

∙ 11/23/2020

Interpretable Visual Reasoning via Induced Symbolic Space

We study the problem of concept induction in visual reasoning, i.e., ide...

Zhonghao Wang, et al. ∙

research

∙ 11/21/2020

Efficient Neural Network Implementation with Quadratic Neuron

Previous works proved that the combination of the linear neuron network ...

Zirui Xu, et al. ∙

research

∙ 10/14/2020

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

High quality AI solutions require joint optimization of AI algorithms, s...

Cong Hao, et al. ∙

research

∙ 10/05/2020

Exploring Semantic Capacity of Terms

We introduce and study semantic capacity of terms. For example, the sema...

Jie Huang, et al. ∙

research

∙ 08/28/2020

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

Existing FPGA-based DNN accelerators typically fall into two design para...

Xiaofan Zhang, et al. ∙

research

∙ 08/24/2020

Tearing Down the Memory Wall

We present a vision for the Erudite architecture that redefines the comp...

Zaid Qureshi, et al. ∙

research

∙ 07/31/2020

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

When the training data are maliciously tampered, the predictions of the ...

Ren Wang, et al. ∙

research

∙ 07/28/2020

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

This paper presents GPU performance optimization and scaling results for...

Mert Hidayetoglu, et al. ∙

research

∙ 07/18/2020

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

Real-time cine magnetic resonance imaging (MRI) plays an increasingly im...

Tianchen Wang, et al. ∙

research

∙ 06/26/2020

Can Quantum Computers Learn Like Classical Computers? A Co-Design Framework for Machine Learning and Quantum Circuits

Despite the pursuit of quantum supremacy in various applications, the po...

Weiwen Jiang, et al. ∙

research

∙ 06/25/2020

Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case

Although graph neural networks (GNNs) have made great progress recently ...

Shuai Zhang, et al. ∙

research

∙ 06/12/2020

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

Modern analytics and recommendation systems are increasingly based on gr...

Seung Won Min, et al. ∙

research

∙ 05/06/2020

A Multi-Perspective Architecture for Semantic Code Search

The ability to match pieces of code to their corresponding natural langu...

Rajarshi Haldar, et al. ∙

research

∙ 05/06/2020

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

High quality AI solutions require joint optimization of AI algorithms an...

Yuhong Li, et al. ∙

research

∙ 04/02/2020

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

Learning segmentation from synthetic data and adapting to real data can ...

Zhonghao Wang, et al. ∙

research

∙ 03/18/2020

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

We consider the problem of unsupervised domain adaptation for semantic s...

Zhonghao Wang, et al. ∙

research

∙ 02/27/2020

Multi-Cycle-Consistent Adversarial Networks for CT Image Denoising

CT image denoising can be treated as an image-to-image translation task ...

Jinglan Liu, et al. ∙

research

∙ 02/26/2020

DLSpec: A Deep Learning Task Exchange Specification

Deep Learning (DL) innovations are being introduced at a rapid pace. How...

Abdul Dakkak, et al. ∙

research

∙ 02/19/2020

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

Machine Learning (ML) and Deep Learning (DL) innovations are being intro...

Abdul Dakkak, et al. ∙

research

∙ 01/08/2020

On Interpretability of Artificial Neural Networks

Deep learning has achieved great successes in many important areas to de...

Fenglei Fan, et al. ∙

research

∙ 12/05/2019

Tensor Recovery from Noisy and Multi-Level Quantized Measurements

Higher-order tensors can represent scores in a rating system, frames in ...

Ren Wang, et al. ∙

research

∙ 12/03/2019

ELFISH: Resource-Aware Federated Learning on Heterogeneous Edge Devices

In this work, we propose ELFISH - a resource-aware federated learning fr...

Zirui Xu, et al. ∙

research

∙ 11/26/2019

Enabling real-time multi-messenger astrophysics discoveries with deep learning

Multi-messenger astrophysics is a fast-growing, interdisciplinary field ...

E. A. Huerta, et al. ∙

research

∙ 11/19/2019

The Design and Implementation of a Scalable DL Benchmarking Platform

The current Deep Learning (DL) landscape is fast-paced and is rife with ...

Cheng Li, et al. ∙

research

∙ 11/18/2019

DLBricks: Composable Benchmark Generation toReduce Deep Learning Benchmarking Effort on CPUs

The past few years have seen a surge of applying Deep Learning (DL) mode...

Cheng Li, et al. ∙

research

∙ 11/18/2019

DLBricks: Composable Benchmark Generation to Reduce Deep Learning Benchmarking Effort on CPUs

The past few years have seen a surge of applying Deep Learning (DL) mode...

Cheng Li, et al. ∙

research

∙ 11/18/2019

DLBricks: Composable Benchmark Generation to Reduce Deep Learning Benchmarking Effort on CPUs (Extended)

The past few years have seen a surge of applying Deep Learning (DL) mode...

Cheng Li, et al. ∙

research

∙ 11/18/2019

NAIS: Neural Architecture and Implementation Search and its Applications in Autonomous Driving

The rapidly growing demands for powerful AI algorithms in many applicati...

Cong Hao, et al. ∙

research

∙ 11/16/2019

Benanza: Automatic μBenchmark Generation to Compute "Lower-bound" Latency and Inform Optimizations of Deep Learning Models on GPUs

As Deep Learning (DL) models have been increasingly used in latency-sens...

Cheng Li, et al. ∙

research

∙ 11/16/2019

Benanza: Automatic uBenchmark Generation to Compute "Lower-bound" Latency and Inform Optimizations of Deep Learning Models on GPUs

As Deep Learning (DL) models have been increasingly used in latency-sens...

Cheng Li, et al. ∙

research

∙ 09/25/2019

PaRe: A Paper-Reviewer Matching Approach Using a Common Topic Space

Finding the right reviewers to assess the quality of conference submissi...

Omer Anjum, et al. ∙

research

∙ 09/20/2019

SkyNet: a Hardware-Efficient Method for Object Detection and Tracking on Embedded Systems

Developing object detection and tracking on resource-constrained embedde...

Xiaofan Zhang, et al. ∙

Jinjun Xiong

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