4 accepted papers
We consider the problem of finding top-$k$ items from a set of $n$ items using actively chosen pairwise comparisons. This problem has been widely studied in machine learning and has widespread applications in recommendation systems, sports, social choice etc. Motivated by applications where there ca…
Hierarchical clustering over graphs is a fundamental task in data mining and machine learning with applications in many domains including phylogenetics, social network analysis, and information retrieval. Specifically, we consider the recently popularized objective function for hierarchical clusteri…
Rank aggregation from pairwise preferences has widespread applications in recommendation systems and information retrieval. Given the enormous economic and societal impact of these applications, and the consequent incentives for malicious players to manipulate ranking outcomes in their favor, an imp…
The problem of rank aggregation from pairwise and multiway comparisons has a wide range of implications, ranging from recommendation systems to sports rankings to social choice. Some of the most popular algorithms for this problem come from the class of spectral ranking algorithms; these include the…