3 citations · 3 across the 6 of their papers we have counts for
6 papers
Individual Fairness in Hierarchical Clustering
Binita Maity, Shrutimoy Das
Hierarchical clustering produces ultrametric representations that impose strong global geometric constraints and may distort local similarities in ways that disproportionately affe…
Private Sketches for Linear Regression
Shrutimoy Das, Debanuj Nayak, Anirban Dasgupta
Linear regression is frequently applied in a variety of domains, some of which might contain sensitive information. This necessitates that the application of these methods does not…
Local Search-based Individually Fair Clustering with Outliers
Binita Maity, Shrutimoy Das, Anirban Dasgupta
In this paper, we present a local search-based algorithm for individually fair clustering in the presence of outliers. We consider the individual fairness definition proposed in Ju…
Linear Programming based Approximation to Individually Fair k-Clustering with Outliers
Binita Maity, Shrutimoy Das, Anirban Dasgupta
Individual fairness guarantees are often desirable properties to have, but they become hard to formalize when the dataset contains outliers. Here, we investigate the problem of dev…
Local Fragments, Global Gains: Subgraph Counting using Graph Neural Networks
Shubhajit Roy, Shrutimoy Das, Binita Maity +2
Subgraph counting is a fundamental task for analyzing structural patterns in graph-structured data, with important applications in domains such as computational biology and social…
Review of Extreme Multilabel Classification
Arpan Dasgupta, Preeti Lamba, Ankita Kushwaha +4
Extreme multi-label classification or XMLC, is an active area of interest in machine learning. Compared to traditional multi-label classification, here the number of labels is extr…