most citedOptimal Virtual Cluster-based Multiprocessor Scheduling

78 citations · 130 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG2020

Learning to Separate Clusters of Adversarial Representations for Robust Adversarial Detection

Byunggill Joe, Jihun Hamm, Sung Ju Hwang +2

Although deep neural networks have shown promising performances on various tasks, they are susceptible to incorrect predictions induced by imperceptibly small perturbations in inpu…

cs.OS202078 cited

Optimal Virtual Cluster-based Multiprocessor Scheduling

Arvind Easwaran, Insik Shin, Insup Lee

Scheduling of constrained deadline sporadic task systems on multiprocessor platforms is an area which has received much attention in the recent past. It is widely believed that fin…

cs.OS202049 cited

Resource Efficient Isolation Mechanisms in Mixed-Criticality Scheduling

Xiaozhe Gu, Arvind Easwaran, Kieu-My Phan +1

Mixed-criticality real-time scheduling has been developed to improve resource utilization while guaranteeing safe execution of critical applications. These studies use optimistic r…

cs.LG2019

Learning to Disentangle Robust and Vulnerable Features for Adversarial Detection

Byunggill Joe, Sung Ju Hwang, Insik Shin

Although deep neural networks have shown promising performances on various tasks, even achieving human-level performance on some, they are shown to be susceptible to incorrect pred…

cs.CR20193 cited

SynFuzz: Efficient Concolic Execution via Branch Condition Synthesis

Wookhyun Han, Md Lutfor Rahman, Yuxuan Chen +3

Concolic execution is a powerful program analysis technique for exploring execution paths in a systematic manner. Compare to random-mutation-based fuzzing, concolic execution is es…