activity
20172020
most citedInferSpark: Statistical Inference at Scale

3 citations · 6 across the 2 of their papers we have counts for

collaborators

6 papers

cs.DB2020

Dash: Scalable Hashing on Persistent Memory

Baotong Lu, Xiangpeng Hao, Tianzheng Wang +1

Byte-addressable persistent memory (PM) brings hash tables the potential of low latency, cheap persistence and instant recovery. The recent advent of Intel Optane DC Persistent Mem…

cs.DB2020

Top-K Deep Video Analytics: A Probabilistic Approach

Ziliang Lai, Chenxia Han, Chris Liu +3

The impressive accuracy of deep neural networks (DNNs) has created great demands on practical analytics over video data. Although efficient and accurate, the latest video analytic…

cs.DC20203 cited

High Performance Depthwise and Pointwise Convolutions on Mobile Devices

Pengfei Zhang, Eric Lo, Baotong Lu

Lightweight convolutional neural networks (e.g., MobileNets) are specifically designed to carry out inference directly on mobile devices. Among the various lightweight models, dept…

cs.DB2018

Towards Self-Tuning Parameter Servers

Chris Liu, Pengfei Zhang, Bo Tang +4

Recent years, many applications have been driven advances by the use of Machine Learning (ML). Nowadays, it is common to see industrial-strength machine learning jobs that involve…

cs.IR2018

Decentralized Search on Decentralized Web

Ziliang Lai, Chris Liu, Eric Lo +2

Decentralized Web, or DWeb, is envisioned as a promising future of the Web. Being decentralized, there are no dedicated web servers in DWeb; Devices that retrieve web contents also…

cs.DB20173 cited

InferSpark: Statistical Inference at Scale

Zhuoyue Zhao, Jialing Pei, Eric Lo +2

The Apache Spark stack has enabled fast large-scale data processing. Despite a rich library of statistical models and inference algorithms, it does not give domain users the abilit…