4 citations · 8 across the 5 of their papers we have counts for
5 papers
FeReX: A Reconfigurable Design of Multi-bit Ferroelectric Compute-in-Memory for Nearest Neighbor Search
Zhicheng Xu, Che-Kai Liu, Chao Li +7
Rapid advancements in artificial intelligence have given rise to transformative models, profoundly impacting our lives. These models demand massive volumes of data to operate effec…
Low Power and Temperature-Resilient Compute-In-Memory Based on Subthreshold-FeFET
Yifei Zhou, Xuchu Huang, Jianyi Yang +4
Compute-in-memory (CiM) is a promising solution for addressing the challenges of artificial intelligence (AI) and the Internet of Things (IoT) hardware such as 'memory wall' issue.…
Robust Learning for Smoothed Online Convex Optimization with Feedback Delay
Pengfei Li, Jianyi Yang, Adam Wierman +1
We study a challenging form of Smoothed Online Convex Optimization, a.k.a. SOCO, including multi-step nonlinear switching costs and feedback delay. We propose a novel machine learn…
SEE-MCAM: Scalable Multi-bit FeFET Content Addressable Memories for Energy Efficient Associative Search
Shengxi Shou, Che-Kai Liu, Sanggeon Yun +7
In this work, we propose SEE-MCAM, scalable and compact multi-bit CAM (MCAM) designs that utilize the three-terminal ferroelectric FET (FeFET) as the proxy. By exploiting the multi…
CryoAlign: feature-based method for global and local 3D alignment of EM density maps
Bintao He, Fa Zhang, Chenjie Feng +3
Advances on cryo-electron imaging technologies have led to a rapidly increasing number of density maps. Alignment and comparison of density maps play a crucial role in interpreting…