228 citations · 232 across the 14 of their papers we have counts for
15 papers
FairProp: Fair Node Representation Learning via Differentiable Propagation Layers
Emmanouil Kariotakis, Aritra Konar
Graph neural networks (GNNs) are the standard tool for node representation learning and are increasingly used in high-stakes settings. Their message-passing backbone, however, can…
FairRARI: A Plug and Play Framework for Fairness-Aware PageRank
Emmanouil Kariotakis, Aritra Konar
PageRank (PR) is a fundamental algorithm in graph machine learning tasks. Owing to the increasing importance of algorithmic fairness, we consider the problem of computing PR vector…
A Scalable and Exact Relaxation for Densest -Subgraph via Error Bounds
Ya Liu, Junbin Liu, Wing-Kin Ma +1
Given an undirected graph and a size parameter , the Densest -Subgraph (DS) problem extracts the subgraph on vertices with the largest number of induced edges. While D…
The Vertex-Attribute-Constrained Densest -Subgraph Problem
Qiheng Lu, Nicholas D. Sidiropoulos, Aritra Konar
Dense subgraph mining is a fundamental technique in graph mining, commonly applied in fraud detection, community detection, product recommendation, and document summarization. In s…
Differentially Private and Scalable Estimation of the Network Principal Component
Alireza Khayatian, Anil Vullikanti, Aritra Konar
Computing the principal component (PC) of the adjacency matrix of an undirected graph has several applications ranging from identifying key vertices for influence maximization and…
Fairness-Aware Dense Subgraph Discovery
Emmanouil Kariotakis, Nicholas D. Sidiropoulos, Aritra Konar
Dense subgraph discovery (DSD) is a key graph mining primitive with myriad applications including finding densely connected communities which are diverse in their vertex compositio…