output
20042021
most citedDetecting Adversarial Samples from Artifacts

366 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions
Showing cs.LGShow all

3 papers · 1 filter

cs.LG2019

Deep Detector Health Management under Adversarial Campaigns

Javier Echauz, Keith Kenemer, Sarfaraz Hussein +4

Machine learning models are vulnerable to adversarial inputs that induce seemingly unjustifiable errors. As automated classifiers are increasingly used in industrial control system…

cs.LG2019★ 2 cited

Collaborative Graph Walk for Semi-supervised Multi-Label Node Classification

Uchenna Akujuobi, Han Yufei, Qiannan Zhang +1

In this work, we study semi-supervised multi-label node classification problem in attributed graphs. Classic solutions to multi-label node classification follow two steps, first le…

cs.LG2019★ 2 cited

Recurrent Attention Walk for Semi-supervised Classification

Uchenna Akujuobi, Qiannan Zhang, Han Yufei +1

In this paper, we study the graph-based semi-supervised learning for classifying nodes in attributed networks, where the nodes and edges possess content information. Recent approac…