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Fully Dynamic Inference with Deep Neural Networks

Jul 29, 2020
Wenhan Xia, Hongxu Yin, Xiaoliang Dai, Niraj K. Jha


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Visual Transformers: Token-based Image Representation and Processing for Computer Vision

Jul 02, 2020
Bichen Wu, Chenfeng Xu, Xiaoliang Dai, Alvin Wan, Peizhao Zhang, Masayoshi Tomizuka, Kurt Keutzer, Peter Vajda


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FBNetV3: Joint Architecture-Recipe Search using Neural Acquisition Function

Jun 07, 2020
Xiaoliang Dai, Alvin Wan, Peizhao Zhang, Bichen Wu, Zijian He, Zhen Wei, Kan Chen, Yuandong Tian, Matthew Yu, Peter Vajda, Joseph E. Gonzalez


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FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions

Apr 12, 2020
Alvin Wan, Xiaoliang Dai, Peizhao Zhang, Zijian He, Yuandong Tian, Saining Xie, Bichen Wu, Matthew Yu, Tao Xu, Kan Chen, Peter Vajda, Joseph E. Gonzalez

* 8 pages, 10 figures, accepted to CVPR 2020 

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STEERAGE: Synthesis of Neural Networks Using Architecture Search and Grow-and-Prune Methods

Dec 12, 2019
Shayan Hassantabar, Xiaoliang Dai, Niraj K. Jha

* 12 pages, 4 figures 

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DiabDeep: Pervasive Diabetes Diagnosis based on Wearable Medical Sensors and Efficient Neural Networks

Oct 11, 2019
Hongxu Yin, Bilal Mukadam, Xiaoliang Dai, Niraj K. Jha


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Incremental Learning Using a Grow-and-Prune Paradigm with Efficient Neural Networks

May 27, 2019
Xiaoliang Dai, Hongxu Yin, Niraj K. Jha


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ChamNet: Towards Efficient Network Design through Platform-Aware Model Adaptation

Dec 21, 2018
Xiaoliang Dai, Peizhao Zhang, Bichen Wu, Hongxu Yin, Fei Sun, Yanghan Wang, Marat Dukhan, Yunqing Hu, Yiming Wu, Yangqing Jia, Peter Vajda, Matt Uyttendaele, Niraj K. Jha


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FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture Search

Dec 14, 2018
Bichen Wu, Xiaoliang Dai, Peizhao Zhang, Yanghan Wang, Fei Sun, Yiming Wu, Yuandong Tian, Peter Vajda, Yangqing Jia, Kurt Keutzer


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NeST: A Neural Network Synthesis Tool Based on a Grow-and-Prune Paradigm

Jun 01, 2018
Xiaoliang Dai, Hongxu Yin, Niraj K. Jha


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Grow and Prune Compact, Fast, and Accurate LSTMs

May 31, 2018
Xiaoliang Dai, Hongxu Yin, Niraj K. Jha


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