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A $k$-ranking of a graph $G$ is a labeling of its vertices from $\{1,\ldots,k\}$ such that any nontrivial path whose endpoints have the same label contains a larger label. The least $k$ for which $G$ has a $k$-ranking is the ranking number…

Combinatorics · Mathematics 2014-01-16 Daniel C. McDonald

Paired comparison data, where users evaluate items in pairs, play a central role in ranking and preference learning tasks. While ordinal comparison data intuitively offer richer information than binary comparisons, this paper challenges…

Machine Learning · Statistics 2026-01-13 Shirong Xu , Jingnan Zhang , Junhui Wang

Rank estimation is a classical model order selection problem that arises in a variety of important statistical signal and array processing systems, yet is addressed relatively infrequently in the extant literature. Here we present sample…

Methodology · Statistics 2011-08-25 Patrick O. Perry , Patrick J. Wolfe

This paper aims at formulating the issue of ranking multivariate unlabeled observations depending on their degree of abnormality as an unsupervised statistical learning task. In the 1-d situation, this problem is usually tackled by means of…

Machine Learning · Statistics 2018-09-05 Stephan Clémençon , Albert Thomas

A new class of general exponential ranking models is introduced which we label angle-based models for ranking data. A consensus score vector is assumed, which assigns scores to a set of items, where the scores reflect a consensus view of…

Methodology · Statistics 2017-12-27 Hang Xu , Mayer Alvo , Philip L. H. Yu

A novel approach for solving a multiple judge, multiple criteria decision making (MCDM) problem is proposed. The ranking of alternatives that are evaluated based on multiple criteria is difficult, since the presence of multiple criteria…

Applications · Statistics 2018-07-17 Daniel Kostner

Discovering the most interesting patterns is the key problem in the field of pattern mining. While ranking or selecting patterns is well-studied for itemsets it is surprisingly under-researched for other, more complex, pattern types. In…

Machine Learning · Computer Science 2019-04-18 Nikolaj Tatti

Policies trained via Reinforcement Learning (RL) are often needlessly complex, making them difficult to analyse and interpret. In a run with $n$ time steps, a policy will make $n$ decisions on actions to take; we conjecture that only a…

Machine Learning · Computer Science 2021-10-27 Hadrien Pouget , Hana Chockler , Youcheng Sun , Daniel Kroening

Comparing the top $k$ elements between two or more ranked results is a common task in many contexts and settings. A few measures have been proposed to compare top $k$ lists with attractive mathematical properties, but they face a number of…

Information Theory · Computer Science 2013-10-02 Arun Konagurthu , James Collier

Matrix rank minimization problems are gaining a plenty of recent attention in both mathematical and engineering fields. This class of problems, arising in various and across-discipline applications, is known to be NP-hard in general. In…

Optimization and Control · Mathematics 2010-10-06 Yun-Bin Zhao

Competition between a complex system's constituents and a corresponding reward mechanism based on it have profound influence on the functioning, stability, and evolution of the system. But determining the dominance hierarchy or ranking…

Physics and Society · Physics 2016-03-25 Juyong Park , Soon-Hyung Yook

In several multiobjective decision problems Pairwise Comparison Matrices (PCM) are applied to evaluate the decision variants. The problem that arises very often is the inconsistency of a given PCM. In such a situation it is important to…

Optimization and Control · Mathematics 2024-12-10 Marcin Anholcer , Janos Fülöp

In this paper, we study the minimum rank among positive semidefinite matrices with a given graph of at most seven vertices (msr) by giving vector representations.

Combinatorics · Mathematics 2012-07-25 Xinyun Zhu

Rankings and scores are two common data types used by judges to express preferences and/or perceptions of quality in a collection of objects. Numerous models exist to study data of each type separately, but no unified statistical model…

Methodology · Statistics 2022-09-02 Michael Pearce , Elena A. Erosheva

We study a ranking and selection problem of learning from choice-based feedback with dynamic assortments. In this problem, a company sequentially displays a set of items to a population of customers and collects their choices as feedback.…

Machine Learning · Computer Science 2025-01-03 Junwen Yang , Yifan Feng

Given pairwise comparisons between multiple items, how to rank them so that the ranking matches the observations? This problem, known as rank aggregation, has found many applications in sports, recommendation systems, and other web…

Machine Learning · Statistics 2023-09-12 Ziliang Samuel Zhong , Shuyang Ling

In modern ranking problems, different and disparate representations of the items to be ranked are often available. It is sensible, then, to try to combine these representations to improve ranking. Indeed, learning to rank via combining…

Chess championships are often organised as a Swiss-system tournament, causing great challenges in ranking the participants due to the different strength of schedules and possible circular triads. The paper suggests that pairwise comparison…

Applications · Statistics 2016-11-03 Lászlo Csató

Referring to a standard context of voting theory, and to the classic notion of voting situation, here we show that it is possible to observe any arbitrary set of elections' outcomes, no matter how paradoxical it may appear. On this purpose…

Probability · Mathematics 2022-06-01 Emilio De Santis , Fabio Spizzichino

In a bivariate setting, we consider the problem of detecting a sparse contamination or mixture component, where the effect manifests itself as a positive dependence between the variables, which are otherwise independent in the main…

Statistics Theory · Mathematics 2020-01-13 Ery Arias-Castro , Rong Huang , Nicolas Verzelen