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Bin Ren
Researcher at Xiamen University
Publications - 528
Citations - 30728
Bin Ren is an academic researcher from Xiamen University. The author has contributed to research in topics: Raman spectroscopy & Surface-enhanced Raman spectroscopy. The author has an hindex of 73, co-authored 470 publications receiving 23452 citations. Previous affiliations of Bin Ren include Pacific Northwest National Laboratory & Max Planck Society.
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BLK-REW: A Unified Block-based DNN Pruning Framework using Reweighted Regularization Method
Xiaolong Ma,Zhengang Li,Yifan Gong,Tianyun Zhang,Wei Niu,Zheng Zhan,Pu Zhao,Jian Tang,Xue Lin,Bin Ren,Yanzhi Wang +10 more
TL;DR: A new block-based pruning framework that comprises a general and flexible structured pruning dimension as well as a powerful and efficient reweighted regularization method that achieves universal coverage for both CNNs and RNNs with real-time mobile acceleration and no accuracy compromise is proposed.
Proceedings Article
Achieving on-Mobile Real-Time Super-Resolution with Neural Architecture and Pruning Search
Zheng Zhan,Yifan Gong,Pu Zhao,Geng Yuan,Wei Niu,Yushu Wu,Tianyun Zhang,Malith Jayaweera,David Kaeli,Bin Ren,Xue Lin,Yanzhi Wang +11 more
TL;DR: Zhang et al. as mentioned in this paper combined neural architecture search with pruning search and proposed an automatic search framework that derives sparse super-resolution models with high image quality while satisfying the real-time inference requirement.
Journal ArticleDOI
Nanobowtie arrays with tunable materials and geometries fabricated by holographic lithography
TL;DR: This THL technique shows unique advantages in fabricating well-defined and large-area nanostructures in a high throughput way, facilitating practical applications in a broad range of fields of optoelectronics.
Posted Content
An Image Enhancing Pattern-based Sparsity for Real-time Inference on Mobile Devices
Xiaolong Ma,Wei Niu,Tianyun Zhang,Sijia Liu,Sheng Lin,Hongjia Li,Xiang Chen,Jian Tang,Kaisheng Ma,Bin Ren,Yanzhi Wang +10 more
TL;DR: This work introduces a new sparsity dimension, namely pattern-based sparsity that comprises pattern and connectivity sparsity, and is the first time that mobile devices achieve real-time inference for the large-scale DNN models thanks to the unique spatial property of pattern- based sparsity and the help of the code generation capability of compilers.