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While machine-learning models are flourishing and transforming many aspects of everyday life, the inability of humans to understand complex models poses difficulties for these models to be fully trusted and embraced. Thus, interpretability…

Artificial Intelligence · Computer Science 2020-06-18 Guangyi Zhang , Aristides Gionis

In this paper, we consider batch supervised learning where an adversary is allowed to corrupt instances with arbitrarily large noise. The adversary is allowed to corrupt any $l$ features in each instance and the adversary can change their…

Machine Learning · Computer Science 2019-07-30 Chris Mesterharm , Rauf Izmailov , Scott Alexander , Simon Tsang

The single transferable vote (STV) is a system of preferential proportional voting employed in multi-seat elections. Each ballot cast by a voter is a (potentially partial) ranking over a set of candidates. The margin of victory, or simply…

Computer Science and Game Theory · Computer Science 2025-03-26 Michelle Blom , Alexander Ek , Peter J. Stuckey , Vanessa Teague , Damjan Vukcevic

A Condorcet voting scheme chooses a winning candidate as one who defeats all others in pairwise majority rule. We provide a review which includes the rigorous mathematical treatment for calculating the limiting probability of a Condorcet…

Statistics Theory · Mathematics 2007-06-13 M. S. Krishnamoorthy , M. Raghavachari

A Condorcet winning set is a set of candidates such that no other candidate is preferred by at least half the voters over all members of the set. The Condorcet dimension, which is the minimum cardinality of a Condorcet winning set, is known…

Computer Science and Game Theory · Computer Science 2025-12-02 Alexandra Lassota , Adrian Vetta , Bernhard von Stengel

Metric learning aims to embed one metric space into another to benefit tasks like classification and clustering. Although a greatly distorted metric space has a high degree of freedom to fit training data, it is prone to overfitting and…

Machine Learning · Computer Science 2015-05-12 Renjie Liao , Jianping Shi , Ziyang Ma , Jun Zhu , Jiaya Jia

The important Kemeny problem, which consists of computing median consensus rankings of an election with respect to the Kemeny voting rule, admits important applications in biology and computational social choice and was generalized recently…

Computer Science and Game Theory · Computer Science 2023-05-01 Xuan Kien Phung , Sylvie Hamel

We show on theoretical grounds that, even in the presence of noise, probabilistic measurement strategies (which have a certain probability of failure or abstention) can provide, upon a heralded successful outcome, estimates with a precision…

Quantum Physics · Physics 2016-10-27 J. Calsamiglia , B. Gendra , R. Munoz-Tapia , E. Bagan

American democracy is currently heavily reliant on plurality in single-member districts, or PSMD, as a system of election. But public perceptions of fairness are often keyed to partisan proportionality, or the degree of congruence between…

Computers and Society · Computer Science 2023-08-23 Moon Duchin , Gabe Schoenbach

We focus on a generalization of the classic Minisum approval voting rule, introduced by Barrot and Lang (2016), and referred to as Conditional Minisum (CMS), for multi-issue elections with preferential dependencies. Under this rule, voters…

Computer Science and Game Theory · Computer Science 2025-06-10 Evangelos Markakis , Georgios Papasotiropoulos

Epistemic social choice aims at unveiling a hidden ground truth given votes, which are interpreted as noisy signals about it. We consider here a simple setting where votes consist of approval ballots: each voter approves a set of…

Computer Science and Game Theory · Computer Science 2021-12-09 Tahar Allouche , Jérôme Lang , Florian Yger

Many high-stakes AI deployments proceed only if every stakeholder deems the system acceptable relative to their own minimum standard. With randomization over a finite menu of options, this becomes a feasibility question: does there exist a…

Computer Science and Game Theory · Computer Science 2026-04-21 Davin Choo , Paul W. Goldberg , Nicholas Teh

Image deblurring is an ill-posed problem with multiple plausible solutions for a given input image. However, most existing methods produce a deterministic estimate of the clean image and are trained to minimize pixel-level distortion. These…

Computer Vision and Pattern Recognition · Computer Science 2021-12-30 Jay Whang , Mauricio Delbracio , Hossein Talebi , Chitwan Saharia , Alexandros G. Dimakis , Peyman Milanfar

We provide deterministic, polynomial-time computable voting rules that approximate Dodgson's and (the ``minimization version'' of) Young's scoring rules to within a logarithmic factor. Our approximation of Dodgson's rule is tight up to a…

Computer Science and Game Theory · Computer Science 2008-12-18 Jason Covey , Christopher Homan

Many real life situations require a set of items to be repeatedly placed in a random sequence. In such circumstances, it is often desirable to test whether such randomization indeed obtains, yet this problem has received very limited…

Applications · Statistics 2023-04-14 Darren Grant

The pop-stack-sorting process is a variation of the stack-sort process. We consider a deterministic version of this process, and provide a new lower bound of $\frac{3}{5}n$ for the number of sorts to fully sort a uniformly randomly chosen…

Combinatorics · Mathematics 2024-08-26 Morgan Bauer , Keith Copenhaver

This paper introduces a novel binary stability property for voting rules-called binary self-selectivity-by which a society considering whether to replace its voting rule using itself in pairwise elections will choose not to do so. In…

Theoretical Economics · Economics 2025-08-27 Héctor Hermida-Rivera , Toygar T. Kerman

In this work we investigate the behavior of the distortion threshold that can be guaranteed in joint source-channel coding, to within a prescribed excess-distortion probability. We show that the gap between this threshold and the optimal…

Information Theory · Computer Science 2011-12-08 Da Wang , Amir Ingber , Yuval Kochman

We consider the problem of matching a metric space $(X,d_X)$ of size $k$ with a subspace of a metric space $(Y,d_Y)$ of size $n \geq k$, assuming that these two spaces have constant doubling dimension $\delta$. More precisely, given an…

Data Structures and Algorithms · Computer Science 2020-12-22 Corentin Allair , Antoine Vigneron

The margin of victory of an election is a useful measure to capture the robustness of an election outcome. It also plays a crucial role in determining the sample size of various algorithms in post election audit, polling etc. In this work,…

Artificial Intelligence · Computer Science 2015-05-05 Palash Dey , Y. Narahari