no code implementations • 20 Feb 2024 • X. San Liang, Dake Chen, Renhe Zhang
It has been said, arguably, that causality analysis should pave a promising way to interpretable deep learning and generalization.
no code implementations • 12 Oct 2023 • Dake Chen, Hanbin Wang, Yunhao Huo, Yuzhao Li, Haoyang Zhang
The large language model (LLM) based agents have demonstrated their capacity to automate and expedite software development processes.
1 code implementation • 13 Sep 2023 • Chenghao Li, Dake Chen, Yuke Zhang, Peter A. Beerel
While diffusion models demonstrate a remarkable capability for generating high-quality images, their tendency to `replicate' training data raises privacy concerns.
no code implementations • 8 Jun 2023 • Dake Chen, Christine Goins, Maxwell Waugaman, Georgios D. Dimou, Peter A. Beerel
In this paper, we describe and analyze an island-based random dynamic voltage scaling (iRDVS) approach to thwart power side-channel attacks.
no code implementations • 26 Apr 2023 • Souvik Kundu, Yuke Zhang, Dake Chen, Peter A. Beerel
Large number of ReLU and MAC operations of Deep neural networks make them ill-suited for latency and compute-efficient private inference.
no code implementations • ICCV 2023 • Yuke Zhang, Dake Chen, Souvik Kundu, Chenghao Li, Peter A. Beerel
Then, given our observation that external attention (EA) presents lower PI latency than widely-adopted self-attention (SA) at the cost of accuracy, we present a selective attention search (SAS) method to integrate the strength of EA and SA.