90 citations · 97 across the 5 of their papers we have counts for
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cs.LG2020
Growing Deep Forests Efficiently with Soft Routing and Learned Connectivity
Jianghao Shen, Sicheng Wang, Zhangyang Wang
Despite the latest prevailing success of deep neural networks (DNNs), several concerns have been raised against their usage, including the lack of intepretability the gap between D…
cs.LG2020★ 7 cited
Fractional Skipping: Towards Finer-Grained Dynamic CNN Inference
Jianghao Shen, Yonggan Fu, Yue Wang +3
While increasingly deep networks are still in general desired for achieving state-of-the-art performance, for many specific inputs a simpler network might already suffice. Existing…
cs.LG2019★ 90 cited
Dual Dynamic Inference: Enabling More Efficient, Adaptive and Controllable Deep Inference
Yue Wang, Jianghao Shen, Ting-Kuei Hu +5
State-of-the-art convolutional neural networks (CNNs) yield record-breaking predictive performance, yet at the cost of high-energy-consumption inference, that prohibits their widel…