Kernel task scheduling is important for application performance, adaptab...
Many machine learning algorithms require large numbers of labeled data t...
High-speed RDMA networks are getting rapidly adopted in the industry for...
In this paper, we propose Adam-Hash: an adaptive and dynamic multi-resol...
There has been a recent effort in applying differential privacy on memor...
K-means++ is an important algorithm to choose initial cluster centers fo...
Over the last decade, deep neural networks have transformed our society,...
The success of deep learning comes at a tremendous computational and ene...
Kernel density estimation (KDE) stands out as a challenging task in mach...
Online bipartite matching is a fundamental problem in online algorithms....
Service meshes play a central role in the modern application ecosystem b...
With the advent of ubiquitous deployment of smart devices and the Intern...
Many deep learning tasks have to deal with graphs (e.g., protein structu...
Inspired by InstaHide challenge [Huang, Song, Li and Arora'20], [Chen, S...
In this work, we examine the security of InstaHide, a scheme recently
pr...
High-performance tensor programs are crucial to guarantee efficient exec...
High development velocity is critical for modern systems. This is especi...
Collective communication systems such as MPI offer high performance grou...
A perennial question in computer networks is where to place functionalit...