most citedFIGARO: Improving System Performance via Fine-Grained In-DRAM Data Relocation and Caching

7 citations · 17 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CR20227 cited

HUT: Enabling High-UTility, Batched Queries under Differential Privacy Protection for Internet-of-Vehicles

Junyu Liu, Wangkai Jin, Zhenyong He +4

The emerging trends of Internet-of-Vehicles (IoV) demand centralized servers to collect/process sensitive data with limited computational resources on a single vehicle. Such centra…

cs.CR20221 cited

Characterizing Differentially-Private Techniques in the Era of Internet-of-Vehicles

Yicun Duan, Junyu Liu, Wangkai Jin +1

Recent developments of advanced Human-Vehicle Interactions rely on the concept Internet-of-Vehicles (IoV), to achieve large-scale communications and synchronizations of data in pra…

cs.HC20221 cited

BROOK Dataset: A Playground for Exploiting Data-Driven Techniques in Human-Vehicle Interactive Designs

Wangkai Jin, Yicun Duan, Junyu Liu +3

Emerging Autonomous Vehicles (AV) breed great potentials to exploit data-driven techniques for adaptive and personalized Human-Vehicle Interactions. However, the lack of high-quali…

cs.AR20207 cited

FIGARO: Improving System Performance via Fine-Grained In-DRAM Data Relocation and Caching

Yaohua Wang, Lois Orosa, Xiangjun Peng +8

DRAM Main memory is a performance bottleneck for many applications due to the high access latency. In-DRAM caches work to mitigate this latency by augmenting regular-latency DRAM w…

cs.HC20201 cited

Building BROOK: A Multi-modal and Facial Video Database for Human-Vehicle Interaction Research

Xiangjun Peng, Zhentao Huang, Xu Sun

With the growing popularity of Autonomous Vehicles, more opportunities have bloomed in the context of Human-Vehicle Interactions. However, the lack of comprehensive and concrete da…