Hsin-Pai Cheng

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Duke University ∙ Hewlett Packard Enterprise

ScaleNAS: One-Shot Learning of Scale-Aware Representations for Visual Recognition

Scale variance among different sizes of body parts and objects is a chal...
11/30/2020 ∙ by Hsin-Pai Cheng, et al. ∙ 0 ∙ share

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NASGEM: Neural Architecture Search via Graph Embedding Method

Neural Architecture Search (NAS) automates and prospers the design of ne...
07/08/2020 ∙ by Hsin-Pai Cheng, et al. ∙ 0 ∙ share

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Ordering Chaos: Memory-Aware Scheduling of Irregularly Wired Neural Networks for Edge Devices

Recent advances demonstrate that irregularly wired neural networks from ...
03/04/2020 ∙ by Byung Hoon Ahn, et al. ∙ 12 ∙ share

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AutoShrink: A Topology-aware NAS for Discovering Efficient Neural Architecture

Resource is an important constraint when deploying Deep Neural Networks ...
11/21/2019 ∙ by Tunhou Zhang, et al. ∙ 0 ∙ share

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Low-Power Computer Vision: Status, Challenges, Opportunities

Computer vision has achieved impressive progress in recent years. Meanwh...
04/15/2019 ∙ by Sergei Alyamkin, et al. ∙ 16 ∙ share

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Towards Leveraging the Information of Gradients in Optimization-based Adversarial Attack

In recent years, deep neural networks demonstrated state-of-the-art perf...
12/06/2018 ∙ by Jingyang Zhang, et al. ∙ 0 ∙ share

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LEASGD: an Efficient and Privacy-Preserving Decentralized Algorithm for Distributed Learning

Distributed learning systems have enabled training large-scale models ov...
11/27/2018 ∙ by Hsin-Pai Cheng, et al. ∙ 0 ∙ share

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Differentiable Fine-grained Quantization for Deep Neural Network Compression

Neural networks have shown great performance in cognitive tasks. When de...
10/20/2018 ∙ by Hsin-Pai Cheng, et al. ∙ 0 ∙ share

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2018 Low-Power Image Recognition Challenge

The Low-Power Image Recognition Challenge (LPIRC, https://rebootingcompu...
10/03/2018 ∙ by Sergei Alyamkin, et al. ∙ 6 ∙ share

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A Multi-strength Adversarial Training Method to Mitigate Adversarial Attacks

Some recent works revealed that deep neural networks (DNNs) are vulnerab...
05/27/2017 ∙ by Chang Song, et al. ∙ 0 ∙ share

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Hsin-Pai Cheng

Featured Co-authors

Xin Liu

Yiran Chen

Hai Li

Bo Chen

Meng Li

Chen Feng

Xiaopeng Zhang

Fei Sun

Yang Lu

Vikas Chandra

Alexander C. Berg

ScaleNAS: One-Shot Learning of Scale-Aware Representations for Visual Recognition

NASGEM: Neural Architecture Search via Graph Embedding Method

Ordering Chaos: Memory-Aware Scheduling of Irregularly Wired Neural Networks for Edge Devices

AutoShrink: A Topology-aware NAS for Discovering Efficient Neural Architecture

Low-Power Computer Vision: Status, Challenges, Opportunities

Towards Leveraging the Information of Gradients in Optimization-based Adversarial Attack

LEASGD: an Efficient and Privacy-Preserving Decentralized Algorithm for Distributed Learning

Differentiable Fine-grained Quantization for Deep Neural Network Compression

2018 Low-Power Image Recognition Challenge

A Multi-strength Adversarial Training Method to Mitigate Adversarial Attacks