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Achieving Fully Proportional Representation is Easy in Practice

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arxiv 1301.6400 v1 pith:UHGGQQOM submitted 2013-01-27 cs.MA cs.GT

Piotr Skowron , Piotr Faliszewski , Arkadii Slinko This is my paper · ORCID
classification cs.MAcs.GT
keywords algorithmsdataveryachievinganalysisapproximateboundscases
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We provide experimental evaluation of a number of known and new algorithms for approximate computation of Monroe's and Chamberlin-Courant's rules. Our experiments, conducted both on real-life preference-aggregation data and on synthetic data, show that even very simple and fast algorithms can in many cases find near-perfect solutions. Our results confirm and complement very recent theoretical analysis of Skowron et al., who have shown good lower bounds on the quality of (some of) the algorithms that we study.

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  1. Efficient inference of rankings from multi-body comparisons

    physics.soc-ph 2025-01 reject novelty 5.0 of 10

    A Newman-style iterative solver for Plackett-Luce rankings is derived and shown to converge in fewer iterations, but the headline claim that multi-body PL beats pairwise projections rests on an invalid likelihood comparison.

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