Search Results for author: Weiwen Jiang

Found 40 papers, 8 papers with code

PristiQ: A Co-Design Framework for Preserving Data Security of Quantum Learning in the Cloud

no code implementations20 Apr 2024 Zhepeng Wang, Yi Sheng, Nirajan Koirala, Kanad Basu, Taeho Jung, Cheng-Chang Lu, Weiwen Jiang

Experimental results on simulation and the actual IBM quantum computer both prove the ability of PristiQ to provide high security for the quantum data while maintaining the model performance in QML.

Cloud Computing Quantum Machine Learning

Edge-InversionNet: Enabling Efficient Inference of InversionNet on Edge Devices

no code implementations14 Oct 2023 Zhepeng Wang, Isaacshubhanand Putla, Weiwen Jiang, Youzuo Lin

Seismic full waveform inversion (FWI) is a widely used technique in geophysics for inferring subsurface structures from seismic data.


A Novel Spatial-Temporal Variational Quantum Circuit to Enable Deep Learning on NISQ Devices

no code implementations19 Jul 2023 Jinyang Li, Zhepeng Wang, Zhirui Hu, Prasanna Date, Ang Li, Weiwen Jiang

The results of the evaluation on the standard dataset for binary classification show that ST-VQC can achieve over 30% accuracy improvement compared with existing VQCs on actual quantum computers.

Binary Classification

QuMoS: A Framework for Preserving Security of Quantum Machine Learning Model

no code implementations23 Apr 2023 Zhepeng Wang, Jinyang Li, Zhirui Hu, Blake Gage, Elizabeth Iwasawa, Weiwen Jiang

We further developed a reinforcement learning-based security engine, which can automatically optimize the model design under the distributed setting, such that a good trade-off between model performance and security can be made.

Neural Architecture Search Quantum Machine Learning

On-Device Unsupervised Image Segmentation

no code implementations24 Feb 2023 Junhuan Yang, Yi Sheng, Yuzhou Zhang, Weiwen Jiang, Lei Yang

What's more, for a larger size image in the BBBC005 dataset, the existing approach cannot be accommodated to Raspberry PI due to out of memory; on the other hand, SegHDC can obtain segmentation results within 3 minutes while achieving a 0. 9587 IoU score.

Image Segmentation Segmentation +2

All-in-One: A Highly Representative DNN Pruning Framework for Edge Devices with Dynamic Power Management

no code implementations9 Dec 2022 Yifan Gong, Zheng Zhan, Pu Zhao, Yushu Wu, Chao Wu, Caiwen Ding, Weiwen Jiang, Minghai Qin, Yanzhi Wang

By re-configuring the model to the corresponding pruning ratio for a specific execution frequency (and voltage), we are able to achieve stable inference speed, i. e., keeping the difference in speed performance under various execution frequencies as small as possible.


QuEst: Graph Transformer for Quantum Circuit Reliability Estimation

1 code implementation30 Oct 2022 Hanrui Wang, Pengyu Liu, Jinglei Cheng, Zhiding Liang, Jiaqi Gu, Zirui Li, Yongshan Ding, Weiwen Jiang, Yiyu Shi, Xuehai Qian, David Z. Pan, Frederic T. Chong, Song Han

Specifically, the TorchQuantum library also supports using data-driven ML models to solve problems in quantum system research, such as predicting the impact of quantum noise on circuit fidelity and improving the quantum circuit compilation efficiency.

Towards Real-Time Temporal Graph Learning

1 code implementation8 Oct 2022 Deniz Gurevin, Mohsin Shan, Tong Geng, Weiwen Jiang, Caiwen Ding, Omer Khan

Prior work operates on pre-collected temporal graph data and is not designed to handle updates on a graph in real-time.

graph construction Graph Learning +3

Towards Sparsification of Graph Neural Networks

1 code implementation11 Sep 2022 Hongwu Peng, Deniz Gurevin, Shaoyi Huang, Tong Geng, Weiwen Jiang, Omer Khan, Caiwen Ding

In this paper, we utilize two state-of-the-art model compression methods (1) train and prune and (2) sparse training for the sparsification of weight layers in GNNs.

Image Classification Link Prediction +4

Quantum Neural Network Compression

no code implementations4 Jul 2022 Zhirui Hu, Peiyan Dong, Zhepeng Wang, Youzuo Lin, Yanzhi Wang, Weiwen Jiang

Model compression, such as pruning and quantization, has been widely applied to optimize neural networks on resource-limited classical devices.

Neural Network Compression Quantization

A Collaboration Strategy in the Mining Pool for Proof-of-Neural-Architecture Consensus

no code implementations5 May 2022 Boyang Li, Qing Lu, Weiwen Jiang, Taeho Jung, Yiyu Shi

In many recent novel blockchain consensuses, the deep learning training procedure becomes the task for miners to prove their workload, thus the computation power of miners will not purely be spent on the hash puzzle.

Neural Architecture Search

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

no code implementations23 Feb 2022 Yi Sheng, Junhuan Yang, Yawen Wu, Kevin Mao, Yiyu Shi, Jingtong Hu, Weiwen Jiang, Lei Yang

Results show that FaHaNa can identify a series of neural networks with higher fairness and accuracy on a dermatology dataset.

Face Recognition Fairness +2

Automated Architecture Search for Brain-inspired Hyperdimensional Computing

no code implementations11 Feb 2022 Junhuan Yang, Yi Sheng, Sizhe Zhang, Ruixuan Wang, Kenneth Foreman, Mikell Paige, Xun Jiao, Weiwen Jiang, Lei Yang

On the Clintox dataset, which tries to learn features from developed drugs that passed/failed clinical trials for toxicity reasons, the searched HDC architecture obtains the state-of-the-art ROC-AUC scores, which are 0. 80% higher than the manually designed HDC and 9. 75% higher than conventional neural networks.

Drug Discovery

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

1 code implementation1 Nov 2021 Bingqian Lu, Jianyi Yang, Weiwen Jiang, Yiyu Shi, Shaolei Ren

A key requirement of efficient hardware-aware NAS is the fast evaluation of inference latencies in order to rank different architectures.

Hardware Aware Neural Architecture Search Neural Architecture Search

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

no code implementations ICCV 2021 Sung-En Chang, Yanyu Li, Mengshu Sun, Weiwen Jiang, Sijia Liu, Yanzhi Wang, Xue Lin

Specifically, this is the first effort to assign mixed quantization schemes and multiple precisions within layers -- among rows of the DNN weight matrix, for simplified operations in hardware inference, while preserving accuracy.

Image Classification Quantization

RADARS: Memory Efficient Reinforcement Learning Aided Differentiable Neural Architecture Search

no code implementations13 Sep 2021 Zheyu Yan, Weiwen Jiang, Xiaobo Sharon Hu, Yiyu Shi

To the best of the authors' knowledge, this is the first DNAS framework that can handle large search spaces with bounded memory usage.

Neural Architecture Search reinforcement-learning +1

Exploration of Quantum Neural Architecture by Mixing Quantum Neuron Designs

no code implementations8 Sep 2021 Zhepeng Wang, Zhiding Liang, Shanglin Zhou, Caiwen Ding, Yiyu Shi, Weiwen Jiang

Experimental results demonstrate that the identified quantum neural architectures with mixed quantum neurons can achieve 90. 62% of accuracy on the MNIST dataset, compared with 52. 77% and 69. 92% on the VQC and QuantumFlow, respectively.

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

no code implementations8 Sep 2021 Zhiding Liang, Zhepeng Wang, Junhuan Yang, Lei Yang, JinJun Xiong, Yiyu Shi, Weiwen Jiang

Specifically, this paper targets quantum neural network (QNN), and proposes to learn the errors in the training phase, so that the identified QNN model can be resilient to noise.

A Compression-Compilation Framework for On-mobile Real-time BERT Applications

no code implementations30 May 2021 Wei Niu, Zhenglun Kong, Geng Yuan, Weiwen Jiang, Jiexiong Guan, Caiwen Ding, Pu Zhao, Sijia Liu, Bin Ren, Yanzhi Wang

In this paper, we propose a compression-compilation co-design framework that can guarantee the identified model to meet both resource and real-time specifications of mobile devices.

Question Answering Text Generation

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

no code implementations12 Feb 2021 Yuhong Song, Weiwen Jiang, Bingbing Li, Panjie Qi, Qingfeng Zhuge, Edwin Hsing-Mean Sha, Sakyasingha Dasgupta, Yiyu Shi, Caiwen Ding

Specifically, RT3 integrates two-level optimizations: First, it utilizes an efficient BP as the first-step compression for resource-constrained mobile devices; then, RT3 heuristically generates a shrunken search space based on the first level optimization and searches multiple pattern sets with diverse sparsity for PP via reinforcement learning to support lightweight software reconfiguration, which corresponds to available frequency levels of DVFS (i. e., hardware reconfiguration).


On the Universal Approximability and Complexity Bounds of Deep Learning in Hybrid Quantum-Classical Computing

no code implementations1 Jan 2021 Weiwen Jiang, Yukun Ding, Yiyu Shi

With the continuously increasing number of quantum bits in quantum computers, there are growing interests in exploring applications that can harvest the power of them.

FGNAS: FPGA-Aware Graph Neural Architecture Search

no code implementations1 Jan 2021 Qing Lu, Weiwen Jiang, Meng Jiang, Jingtong Hu, Sakyasingha Dasgupta, Yiyu Shi

The success of gragh neural networks (GNNs) in the past years has aroused grow-ing interest and effort in designing best models to handle graph-structured data.

Neural Architecture Search

DNA: Differentiable Network-Accelerator Co-Search

no code implementations28 Oct 2020 Yongan Zhang, Yonggan Fu, Weiwen Jiang, Chaojian Li, Haoran You, Meng Li, Vikas Chandra, Yingyan Lin

Powerful yet complex deep neural networks (DNNs) have fueled a booming demand for efficient DNN solutions to bring DNN-powered intelligence into numerous applications.

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

no code implementations16 Sep 2020 Sung-En Chang, Yanyu Li, Mengshu Sun, Weiwen Jiang, Runbin Shi, Xue Lin, Yanzhi Wang

To tackle the limited computing and storage resources in edge devices, model compression techniques have been widely used to trim deep neural network (DNN) models for on-device inference execution.

Edge-computing Image Denoising +2

Real-Time Execution of Large-scale Language Models on Mobile

no code implementations15 Sep 2020 Wei Niu, Zhenglun Kong, Geng Yuan, Weiwen Jiang, Jiexiong Guan, Caiwen Ding, Pu Zhao, Sijia Liu, Bin Ren, Yanzhi Wang

Our framework can guarantee the identified model to meet both resource and real-time specifications of mobile devices, thus achieving real-time execution of large transformer-based models like BERT variants.


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

no code implementations17 Aug 2020 Dewen Zeng, Weiwen Jiang, Tianchen Wang, Xiaowei Xu, Haiyun Yuan, Meiping Huang, Jian Zhuang, Jingtong Hu, Yiyu Shi

Experimental results on ACDC MICCAI 2017 dataset demonstrate that our hardware-aware multi-scale NAS framework can reduce the latency by up to 3. 5 times and satisfy the real-time constraints, while still achieving competitive segmentation accuracy, compared with the state-of-the-art NAS segmentation framework.

MRI segmentation Neural Architecture Search +1

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

1 code implementation17 Jul 2020 Weiwen Jiang, Lei Yang, Sakyasingha Dasgupta, Jingtong Hu, Yiyu Shi

To tackle this issue, HotNAS builds a chain of tools to design hardware to support compression, based on which a global optimizer is developed to automatically co-search all the involved search spaces.

Neural Architecture Search

BUNET: Blind Medical Image Segmentation Based on Secure UNET

no code implementations14 Jul 2020 Song Bian, Xiaowei Xu, Weiwen Jiang, Yiyu Shi, Takashi Sato

The strict security requirements placed on medical records by various privacy regulations become major obstacles in the age of big data.

Image Segmentation Medical Image Segmentation +2

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

no code implementations13 Jul 2020 Xingang Yan, Weiwen Jiang, Yiyu Shi, Cheng Zhuo

The recent breakthroughs of Neural Architecture Search (NAS) have motivated various applications in medical image segmentation.

Image Segmentation Medical Image Segmentation +3

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

3 code implementations26 Jun 2020 Weiwen Jiang, JinJun Xiong, Yiyu Shi

We discover that, in order to make full use of the strength of quantum representation, it is best to represent data in a neural network as either random variables or numbers in unitary matrices, such that they can be directly operated by the basic quantum logical gates.

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

no code implementations10 Feb 2020 Lei Yang, Zheyu Yan, Meng Li, Hyoukjun Kwon, Liangzhen Lai, Tushar Krishna, Vikas Chandra, Weiwen Jiang, Yiyu Shi

Neural Architecture Search (NAS) has demonstrated its power on various AI accelerating platforms such as Field Programmable Gate Arrays (FPGAs) and Graphic Processing Units (GPUs).

Neural Architecture Search

NASS: Optimizing Secure Inference via Neural Architecture Search

no code implementations30 Jan 2020 Song Bian, Weiwen Jiang, Qing Lu, Yiyu Shi, Takashi Sato

Due to increasing privacy concerns, neural network (NN) based secure inference (SI) schemes that simultaneously hide the client inputs and server models attract major research interests.

Neural Architecture Search

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

no code implementations31 Oct 2019 Weiwen Jiang, Qiuwen Lou, Zheyu Yan, Lei Yang, Jingtong Hu, Xiaobo Sharon Hu, Yiyu Shi

In this paper, we are the first to bring the computing-in-memory architecture, which can easily transcend the memory wall, to interplay with the neural architecture search, aiming to find the most efficient neural architectures with high network accuracy and maximized hardware efficiency.

Neural Architecture Search

On Neural Architecture Search for Resource-Constrained Hardware Platforms

no code implementations31 Oct 2019 Qing Lu, Weiwen Jiang, Xiaowei Xu, Yiyu Shi, Jingtong Hu

With 30, 000 LUTs, a light-weight design is found to achieve 82. 98\% accuracy and 1293 images/second throughput, compared to which, under the same constraints, the traditional method even fails to find a valid solution.

Neural Architecture Search Quantization +1

Hardware/Software Co-Exploration of Neural Architectures

1 code implementation6 Jul 2019 Weiwen Jiang, Lei Yang, Edwin Sha, Qingfeng Zhuge, Shouzhen Gu, Sakyasingha Dasgupta, Yiyu Shi, Jingtong Hu

We propose a novel hardware and software co-exploration framework for efficient neural architecture search (NAS).

Neural Architecture Search

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

no code implementations31 Jan 2019 Weiwen Jiang, Xinyi Zhang, Edwin H. -M. Sha, Lei Yang, Qingfeng Zhuge, Yiyu Shi, Jingtong Hu

In addition, with a performance abstraction model to analyze the latency of neural architectures without training, our framework can quickly prune architectures that do not satisfy the specification, leading to higher efficiency.

Neural Architecture Search

Cannot find the paper you are looking for? You can Submit a new open access paper.