activity
20182022
most citedMEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge

41 citations · 92 across the 9 of their papers we have counts for

collaborators

15 papers

cs.CV20223 cited

Data-Model-Circuit Tri-Design for Ultra-Light Video Intelligence on Edge Devices

Yimeng Zhang, Akshay Karkal Kamath, Qiucheng Wu +6

In this paper, we propose a data-model-hardware tri-design framework for high-throughput, low-cost, and high-accuracy multi-object tracking (MOT) on High-Definition (HD) video stre…

cs.LG20221 cited

Quarantine: Sparsity Can Uncover the Trojan Attack Trigger for Free

Tianlong Chen, Zhenyu Zhang, Yihua Zhang +3

Trojan attacks threaten deep neural networks (DNNs) by poisoning them to behave normally on most samples, yet to produce manipulated results for inputs attached with a particular t…

cs.LG20224 cited

CryoRL: Reinforcement Learning Enables Efficient Cryo-EM Data Collection

Quanfu Fan, Yilai Li, Yuguang Yao +4

Single-particle cryo-electron microscopy (cryo-EM) has become one of the mainstream structural biology techniques because of its ability to determine high-resolution structures of…

cs.CV2022

Proactive Image Manipulation Detection

Vishal Asnani, Xi Yin, Tal Hassner +2

Image manipulation detection algorithms are often trained to discriminate between images manipulated with particular Generative Models (GMs) and genuine/real images, yet generalize…

cs.LG20221 cited

Optimizer Amalgamation

Tianshu Huang, Tianlong Chen, Sijia Liu +3

Selecting an appropriate optimizer for a given problem is of major interest for researchers and practitioners. Many analytical optimizers have been proposed using a variety of theo…

cs.LG2021

RMSMP: A Novel Deep Neural Network Quantization Framework with Row-wise Mixed Schemes and Multiple Precisions

Sung-En Chang, Yanyu Li, Mengshu Sun +4

This work proposes a novel Deep Neural Network (DNN) quantization framework, namely RMSMP, with a Row-wise Mixed-Scheme and Multi-Precision approach. Specifically, this is the firs…