b'Weiwen Jiang'

research

∙ 09/22/2022

Iterative Qubits Management for Quantum Index Searching in a Hybrid System

Recent advances in quantum computing systems attract tremendous attentio...

Wenrui Mu, et al. ∙

research

∙ 09/11/2022

Towards Sparsification of Graph Neural Networks

As real-world graphs expand in size, larger GNN models with billions of ...

Hongwu Peng, et al. ∙

research

∙ 08/07/2022

A Length Adaptive Algorithm-Hardware Co-design of Transformer on FPGA Through Sparse Attention and Dynamic Pipelining

Transformers are considered one of the most important deep learning mode...

Hongwu Peng, et al. ∙

research

∙ 07/28/2022

VACSEN: A Visualization Approach for Noise Awareness in Quantum Computing

Quantum computing has attracted considerable public attention due to its...

Shaolun Ruan, et al. ∙

research

∙ 07/04/2022

Quantum Neural Network Compression

Model compression, such as pruning and quantization, has been widely app...

Zhirui Hu, et al. ∙

research

∙ 02/23/2022

The Larger The Fairer? Small Neural Networks Can Achieve Fairness for Edge Devices

Along with the progress of AI democratization, neural networks are being...

Yi Sheng, et al. ∙

research

∙ 02/11/2022

Automated Architecture Search for Brain-inspired Hyperdimensional Computing

This paper represents the first effort to explore an automated architect...

Junhuan Yang, et al. ∙

research

∙ 11/01/2021

One Proxy Device Is Enough for Hardware-Aware Neural Architecture Search

Convolutional neural networks (CNNs) are used in numerous real-world app...

Bingqian Lu, et al. ∙

research

∙ 10/30/2021

RMSMP: A Novel Deep Neural Network Quantization Framework with Row-wise Mixed Schemes and Multiple Precisions

This work proposes a novel Deep Neural Network (DNN) quantization framew...

Sung-En Chang, et al. ∙

research

∙ 10/15/2021

Detecting Gender Bias in Transformer-based Models: A Case Study on BERT

In this paper, we propose a novel gender bias detection method by utiliz...

Bingbing Li, et al. ∙

research

∙ 09/13/2021

Optimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search

Molecular similarity search has been widely used in drug discovery to id...

Hongwu Peng, et al. ∙

research

∙ 09/13/2021

RADARS: Memory Efficient Reinforcement Learning Aided Differentiable Neural Architecture Search

Differentiable neural architecture search (DNAS) is known for its capaci...

Zheyu Yan, 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

∙ 02/12/2021

Dancing along Battery: Enabling Transformer with Run-time Reconfigurability on Mobile Devices

A pruning-based AutoML framework for run-time reconfigurability, namely ...

Yuhong Song, 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

∙ 10/28/2020

DNA: Differentiable Network-Accelerator Co-Search

Powerful yet complex deep neural networks (DNNs) have fueled a booming d...

Yongan Zhang, et al. ∙

research

∙ 09/16/2020

MSP: An FPGA-Specific Mixed-Scheme, Multi-Precision Deep Neural Network Quantization Framework

With the tremendous success of deep learning, there exists imminent need...

Sung-En Chang, et al. ∙

research

∙ 08/17/2020

Towards Cardiac Intervention Assistance: Hardware-aware Neural Architecture Exploration for Real-Time 3D Cardiac Cine MRI Segmentation

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

Dewen Zeng, et al. ∙

research

∙ 07/17/2020

Standing on the Shoulders of Giants: Hardware and Neural Architecture Co-Search with Hot Start

Hardware and neural architecture co-search that automatically generates ...

Weiwen Jiang, et al. ∙

research

∙ 07/14/2020

BUNET: Blind Medical Image Segmentation Based on Secure UNET

The strict security requirements placed on medical records by various pr...

Song Bian, et al. ∙

research

∙ 07/13/2020

MS-NAS: Multi-Scale Neural Architecture Search for Medical Image Segmentation

The recent breakthroughs of Neural Architecture Search (NAS) have motiva...

Xingang Yan, 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

∙ 02/10/2020

Co-Exploration of Neural Architectures and Heterogeneous ASIC Accelerator Designs Targeting Multiple Tasks

Neural Architecture Search (NAS) has demonstrated its power on various A...

Lei Yang, et al. ∙

research

∙ 01/30/2020

NASS: Optimizing Secure Inference via Neural Architecture Search

Due to increasing privacy concerns, neural network (NN) based secure inf...

Song Bian, et al. ∙

research

∙ 10/31/2019

Device-Circuit-Architecture Co-Exploration for Computing-in-Memory Neural Accelerators

Co-exploration of neural architectures and hardware design is promising ...

Weiwen Jiang, et al. ∙

research

∙ 10/31/2019

On Neural Architecture Search for Resource-Constrained Hardware Platforms

In the recent past, the success of Neural Architecture Search (NAS) has ...

Qing Lu, et al. ∙

research

∙ 07/21/2019

Achieving Super-Linear Speedup across Multi-FPGA for Real-Time DNN Inference

Real-time Deep Neural Network (DNN) inference with low-latency requireme...

Weiwen Jiang, et al. ∙

research

∙ 07/06/2019

Hardware/Software Co-Exploration of Neural Architectures

We propose a novel hardware and software co-exploration framework for ef...

Weiwen Jiang, et al. ∙

research

∙ 01/31/2019

Accuracy vs. Efficiency: Achieving Both through FPGA-Implementation Aware Neural Architecture Search

A fundamental question lies in almost every application of deep neural n...

Weiwen Jiang, et al. ∙

Weiwen Jiang

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