most citedHandling Adversarial Concept Drift in Streaming Data

75 citations · 138 across the 5 of their papers we have counts for

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stat.ML2017

On the Reliable Detection of Concept Drift from Streaming Unlabeled Data

Tegjyot Singh Sethi, Mehmed Kantardzic

Classifiers deployed in the real world operate in a dynamic environment, where the data distribution can change over time. These changes, referred to as concept drift, can cause th…

stat.ML2017★ 47 cited

Data Driven Exploratory Attacks on Black Box Classifiers in Adversarial Domains

Tegjyot Singh Sethi, Mehmed Kantardzic

While modern day web applications aim to create impact at the civilization level, they have become vulnerable to adversarial activity, where the next cyber-attack can take any shap…