20 citations · 31 across the 6 of their papers we have counts for
5 papers · 1 filter
Fairness Degrading Adversarial Attacks Against Clustering Algorithms
Anshuman Chhabra, Adish Singla, Prasant Mohapatra
Clustering algorithms are ubiquitous in modern data science pipelines, and are utilized in numerous fields ranging from biology to facility location. Due to their widespread use, e…
Fair Clustering Using Antidote Data
Anshuman Chhabra, Adish Singla, Prasant Mohapatra
Clustering algorithms are widely utilized for many modern data science applications. This motivates the need to make outputs of clustering algorithms fair. Traditionally, new fair…
Fair Algorithms for Hierarchical Agglomerative Clustering
Anshuman Chhabra, Prasant Mohapatra
Hierarchical Agglomerative Clustering (HAC) algorithms are extensively utilized in modern data science, and seek to partition the dataset into clusters while generating a hierarchi…
Suspicion-Free Adversarial Attacks on Clustering Algorithms
Anshuman Chhabra, Abhishek Roy, Prasant Mohapatra
Clustering algorithms are used in a large number of applications and play an important role in modern machine learning-- yet, adversarial attacks on clustering algorithms seem to b…
Strong Black-box Adversarial Attacks on Unsupervised Machine Learning Models
Anshuman Chhabra, Abhishek Roy, Prasant Mohapatra
Machine Learning (ML) and Deep Learning (DL) models have achieved state-of-the-art performance on multiple learning tasks, from vision to natural language modelling. With the growi…