Weiwen Jiang

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University of Notre Dame ∙ University of Pittsburgh

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

A pruning-based AutoML framework for run-time reconfigurability, namely ...
02/12/2021 ∙ by Yuhong Song, et al. ∙ 8 ∙ share

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When Machine Learning Meets Quantum Computers: A Case Study

Along with the development of AI democratization, the machine learning a...
12/18/2020 ∙ by Weiwen Jiang, et al. ∙ 106 ∙ share

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DNA: Differentiable Network-Accelerator Co-Search

Powerful yet complex deep neural networks (DNNs) have fueled a booming d...
10/28/2020 ∙ by Yongan Zhang, et al. ∙ 0 ∙ share

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

With the tremendous success of deep learning, there exists imminent need...
09/16/2020 ∙ by Sung-En Chang, et al. ∙ 0 ∙ share

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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...
08/17/2020 ∙ by Dewen Zeng, et al. ∙ 0 ∙ share

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

Hardware and neural architecture co-search that automatically generates ...
07/17/2020 ∙ by Weiwen Jiang, et al. ∙ 9 ∙ share

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BUNET: Blind Medical Image Segmentation Based on Secure UNET

The strict security requirements placed on medical records by various pr...
07/14/2020 ∙ by Song Bian, et al. ∙ 0 ∙ share

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

The recent breakthroughs of Neural Architecture Search (NAS) have motiva...
07/13/2020 ∙ by Xingang Yan, et al. ∙ 0 ∙ share

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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...
06/26/2020 ∙ by Weiwen Jiang, et al. ∙ 0 ∙ share

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

Neural Architecture Search (NAS) has demonstrated its power on various A...
02/10/2020 ∙ by Lei Yang, et al. ∙ 0 ∙ share

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NASS: Optimizing Secure Inference via Neural Architecture Search

Due to increasing privacy concerns, neural network (NN) based secure inf...
01/30/2020 ∙ by Song Bian, et al. ∙ 0 ∙ share

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

Co-exploration of neural architectures and hardware design is promising ...
10/31/2019 ∙ by Weiwen Jiang, et al. ∙ 7 ∙ share

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On Neural Architecture Search for Resource-Constrained Hardware Platforms

In the recent past, the success of Neural Architecture Search (NAS) has ...
10/31/2019 ∙ by Qing Lu, et al. ∙ 10 ∙ share

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

Real-time Deep Neural Network (DNN) inference with low-latency requireme...
07/21/2019 ∙ by Weiwen Jiang, et al. ∙ 1 ∙ share

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Hardware/Software Co-Exploration of Neural Architectures

We propose a novel hardware and software co-exploration framework for ef...
07/06/2019 ∙ by Weiwen Jiang, et al. ∙ 9 ∙ share

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

A fundamental question lies in almost every application of deep neural n...
01/31/2019 ∙ by Weiwen Jiang, et al. ∙ 1 ∙ share

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