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We present an algorithm for minimizing the sum of a strongly convex time-varying function with a time-invariant, convex, and nonsmooth function. The proposed algorithm employs the prediction-correction scheme alongside the forward-backward…

Optimization and Control · Mathematics 2024-05-07 Nicola Bastianello , Andrea Simonetto , Ruggero Carli

We study the joint asymptotics of forward and backward processes of numbers of non-empty urns in an infinite urn scheme. The probabilities of balls hitting the urns are assumed to satisfy the conditions of regular decrease. We prove weak…

Probability · Mathematics 2022-11-10 Mikhail Chebunin , Artyom Kovalevskii

We characterize ex-post implementable allocation rules for single object auctions under quasi-linear preferences with convex interdependent value functions. We show that requiring ex-post implementability is equivalent to requiring that the…

Theoretical Economics · Economics 2021-08-24 Saurav Goyal , Aroon Narayanan

We consider multi-task learning, which simultaneously learns related prediction tasks, to improve generalization performance. We factorize a coefficient matrix as the product of two matrices based on a low-rank assumption. These matrices…

Machine Learning · Statistics 2018-08-14 Jun-Yong Jeong , Chi-Hyuck Jun

Consider the decision-making setting where agents elect a panel by expressing both positive and negative preferences. Prominently, in constitutional AI, citizens democratically select a slate of ethical preferences on which a foundation…

Computer Science and Game Theory · Computer Science 2025-03-05 Sonja Kraiczy , Georgios Papasotiropoulos , Grzegorz Pierczyński , Piotr Skowron

We consider a composite convex minimization problem associated with regularized empirical risk minimization, which often arises in machine learning. We propose two new stochastic gradient methods that are based on stochastic dual averaging…

Optimization and Control · Mathematics 2016-03-09 Tomoya Murata , Taiji Suzuki

Despite extensive theoretical research on proportionality in approval-based multiwinner voting, its impact on which committees and candidates can be selected in practice remains poorly understood. We address this gap by (i) analyzing the…

Computer Science and Game Theory · Computer Science 2025-11-13 Niclas Boehmer , Lara Glessen , Jannik Peters

Dual averaging-type methods are widely used in industrial machine learning applications due to their ability to promoting solution structure (e.g., sparsity) efficiently. In this paper, we propose a novel accelerated dual-averaging…

Optimization and Control · Mathematics 2020-01-17 Conghui Tan , Yuqiu Qian , Shiqian Ma , Tong Zhang

We present theoretical and empirical results demonstrating the usefulness of voting rules for participatory democracies. We first give algorithms which efficiently elicit \epsilon-approximations to two prominent voting rules: the Borda rule…

Multiagent Systems · Computer Science 2014-07-17 David Lee , Ashish Goel , Tanja Aitamurto , Helene Landemore

Consider elections where the set of candidates is partitioned into parties, and each party must nominate exactly one candidate. The Possible President problem asks whether some candidate of a given party can become the winner of the…

Computer Science and Game Theory · Computer Science 2025-02-06 Ildikó Schlotter , Katarína Cechlárová

We consider a two-round election model involving $m$ voters and $n$ candidates. Each voter is endowed with a strict preference list ranking the candidates. In the first round, the candidates are partitioned into two subsets, $A$ and $B$,…

Computer Science and Game Theory · Computer Science 2026-03-17 Emilio De Santis , Antonio Di Crescenzo , Verdiana Mustaro

Within the ViSE (Voting in Stochastic Environment) model, we study the effectiveness of majority voting in various environments. As shown by the pit-of-losses paradox identified in previous work, majority decisions in apparently hostile…

Physics and Society · Physics 2025-12-23 Pavel Chebotarev , Vadim Afonkin

We study a class of elections in which the input format is trichotomous and allows voters to elicit their negative feelings explicitly. In particular, we study multiwinner elections with a special proclivity to elect proportionally…

Computer Science and Game Theory · Computer Science 2021-01-14 Nimrod Talmon , Rutvik Page

The symmetric exclusion process and the voter model are two interacting particle systems for which a dual finite particle system allows one to characterize its invariant measures. Adding spontaneous births and deaths to the two processes…

Probability · Mathematics 2007-05-23 Paul Jung

We introduce a general framework for exploring the problem of selecting a committee of representatives with the aim of studying a networked voting rule based on a decentralized large-scale platform, which can assure a strong accountability…

Physics and Society · Physics 2018-01-17 Alexis R. Hernandez , Carlos Gracia-Lazaro , Edgardo Brigatti , Yamir Moreno

The classical alternating minimization (or projection) algorithm has been successful in the context of solving optimization problems over two variables. The iterative nature and simplicity of the algorithm has led to its application to many…

Information Theory · Computer Science 2010-08-24 Urs Niesen , Devavrat Shah , Gregory Wornell

In the apportionment problem, a fixed number of seats must be distributed among parties in proportion to the number of voters supporting each party. We study a generalization of this setting, in which voters can support multiple parties by…

Computer Science and Game Theory · Computer Science 2022-03-31 Markus Brill , Paul Gölz , Dominik Peters , Ulrike Schmidt-Kraepelin , Kai Wilker

This paper considers elections in which voters choose one candidate each, independently according to known probability distributions. A candidate receiving a strict majority (absolute or relative, depending on the version) wins. After the…

Data Structures and Algorithms · Computer Science 2024-01-22 Lisa Hellerstein , Naifeng Liu , Kevin Schewior

Convex combinations of i.i.d. random variables without a finite mean can behave in a strikingly different way from the finite-mean case: as the weight vector becomes more balanced, the resulting combination may become stochastically larger,…

Methodology · Statistics 2026-03-10 Tommaso Lando , Paulo Eduardo Oliveira

We introduce the notion of {\em Distance Restricted Manipulation}, where colluding manipulator(s) need to compute if there exist votes which make their preferred alternative win the election when their knowledge about the others' votes is a…

Computer Science and Game Theory · Computer Science 2020-11-30 Aditya Anand , Palash Dey
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