5 papers
Ulam Rank Aggregation Is Hard to Approximate for Four Rankings
Sk Ruhul Azgor, Diptarka Chakraborty, Le Van Cuong +3
We study the approximability of rank aggregation under the Ulam metric. In the \emph{Ulam median} problem, the goal is to find a ranking (permutation) minimizing the sum of its Ula…
Hardness of Approximation of Rank Aggregation on Ulam Metric
Sk Ruhul Azgor, Diptarka Chakraborty, Le Van Cuong +2
We study the approximability of rank aggregation under the Ulam metric. In the \emph{Ulam median} problem, the goal is to find a permutation minimizing the sum of its Ulam distance…
A Scalable and Unified Framework to Weighted Rank Aggregation
Amir Carmel, Debarati Das, Tien-Long Nguyen
The rank aggregation problem seeks to combine multiple rank orderings of the same set of candidates into a single consensus ordering. Such problems arise in diverse domains, includ…
A Generic Framework for Fair Consensus Clustering in Streams
Diptarka Chakraborty, Kushagra Chatterjee, Debarati Das +1
Consensus clustering seeks to combine multiple clusterings of the same dataset, potentially derived by considering various non-sensitive attributes by different agents in a multi-a…
Towards Fair Representation: Clustering and Consensus
Diptarka Chakraborty, Kushagra Chatterjee, Debarati Das +2
Consensus clustering, a fundamental task in machine learning and data analysis, aims to aggregate multiple input clusterings of a dataset, potentially based on different non-sensit…