Learning Combinatorial Functions from Pairwise Comparisons

Passive and Active Ranking from Pairwise Comparisons

In the problem of ranking from pairwise comparisons, the learner has access to pairwise preferences among n objects and is expected to output a total order of these objects. This problem has a wide range of applications not only in computer science but also in other areas such as social science and economics. In this report, we will give a survey of passive and active learning algorithms for ra...

Learning to Top-K Search using Pairwise Comparisons

Given a collection of N items with some unknown underlying ranking, we examine how to use pairwise comparisons to determine the top ranked items in the set. Resolving the top items from pairwise comparisons has application in diverse fields ranging from recommender systems to image-based search to protein structure analysis. In this paper we introduce techniques to resolve the top ranked items ...

Finite Groups With a Certain Number of Elements Pairwise Generating a Non-Nilpotent Subgroup

When can we rank well from comparisons of \(O(n\log(n))\) non-actively chosen pairs?

Ranking from pairwise comparisons is a ubiquitous problem and has been studied in disciplines ranging from statistics to operations research and from theoretical computer science to machine learning. Here we consider a general setting where outcomes of pairwise comparisons between items i and j are drawn probabilistically by flipping a coin with unknown bias Pij , and ask under what conditions ...

Modeling Expressed Emotions in Music using Pairwise Comparisons

We introduce a two-alternative forced-choice experimental paradigm to quantify expressed emotions in music using the two wellknown arousal and valence (AV) dimensions. In order to produce AV scores from the pairwise comparisons and to visualize the locations of excerpts in the AV space, we introduce a flexible Gaussian process (GP) framework which learns from the pairwise comparisons directly. ...