K
Kaisheng Ma
Researcher at Tsinghua University
Publications - 100
Citations - 2629
Kaisheng Ma is an academic researcher from Tsinghua University. The author has contributed to research in topics: Computer science & Pruning (decision trees). The author has an hindex of 20, co-authored 73 publications receiving 1513 citations. Previous affiliations of Kaisheng Ma include Pennsylvania State University & Peking University.
Papers
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Proceedings ArticleDOI
Be Your Own Teacher: Improve the Performance of Convolutional Neural Networks via Self Distillation
TL;DR: A general training framework named self distillation, which notably enhances the performance of convolutional neural networks through shrinking the size of the network rather than aggrandizing it, and can also provide flexibility of depth-wise scalable inference on resource-limited edge devices.
Proceedings ArticleDOI
Architecture exploration for ambient energy harvesting nonvolatile processors
Kaisheng Ma,Yang Zheng,Shuangchen Li,Karthik Swaminathan,Xueqing Li,Yongpan Liu,Jack Sampson,Yuan Xie,Vijaykrishnan Narayanan +8 more
TL;DR: The simulation platform in this paper is calibrated using measured results from a fabricated nonvolatile processor and used to explore the design space for a nonVolatile processor with different architectures, different input power sources, and policies for maximizing forward progress.
Proceedings ArticleDOI
Ambient energy harvesting nonvolatile processors: from circuit to system
Yongpan Liu,Zewei Li,Hehe Li,Yiqun Wang,Xueqing Li,Kaisheng Ma,Shuangchen Li,Meng-Fan Chang,Jack Sampson,Yuan Xie,Jiwu Shu,Huazhong Yang +11 more
TL;DR: New metrics of nonvolatile processors to consider energy harvesting factors for the first time are proposed and the nonvolatility processor design from circuit to system level is explored.
Proceedings ArticleDOI
Nonvolatile memory design based on ferroelectric FETs
Sumitha George,Kaisheng Ma,Ahmedullah Aziz,Xueqing Li,Asif Islam Khan,Sayeef Salahuddin,Meng-Fan Chang,Suman Datta,Jack Sampson,Sumeet Kumar Gupta,Vijaykrishnan Narayanan +10 more
TL;DR: This work proposes a 2-transistor (2T) FEFET-based nonvolatile memory with separate read and write paths that achieves non-destructive read and lower write power at iso-write speed compared to standard FE-RAM.
Proceedings ArticleDOI
Adversarial Robustness vs. Model Compression, or Both?
Shaokai Ye,Xue Lin,Kaidi Xu,Sijia Liu,Hao Cheng,Jan-Henrik Lambrechts,Huan Zhang,Aojun Zhou,Kaisheng Ma,Yanzhi Wang +9 more
TL;DR: The authors proposed a framework of concurrent adversarial training and weight pruning that enables model compression while still preserving the adversarial robustness and essentially tackles the dilemma of adversarial learning, which is well known that deep neural networks are vulnerable to adversarial attacks, which are implemented by adding crafted perturbations onto benign examples.