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Most work on manipulation assumes that all preferences are known to the manipulators. However, in many settings elections are open and sequential, and manipulators may know the already cast votes but may not know the future votes. We…

Computer Science and Game Theory · Computer Science 2015-03-20 Edith Hemaspaandra , Lane A. Hemaspaandra , Joerg Rothe

The paper considers the problem of finding the number of dominant voters in two-level voting procedures. At the first stage, voting is conducted among local groups of voters, and at the second stage, the results are aggregated to form a…

Discrete Mathematics · Computer Science 2025-06-11 N. I. Shushko , D. V. Lemtyuzhnikova

Given a set of agents with approval preferences over each other, we study the task of finding $k$ matchings fairly representing everyone's preferences. We model the problem as an approval-based multiwinner election where the set of…

Computer Science and Game Theory · Computer Science 2021-02-16 Niclas Boehmer , Markus Brill , Ulrike Schmidt-Kraepelin

The PC algorithm is the state-of-the-art algorithm for causal structure discovery on observational data. It can be computationally expensive in the worst case due to the conditional independence tests are performed in an…

Machine Learning · Computer Science 2021-09-13 Kai Zhang , Chao Tian , Kun Zhang , Todd Johnson , Xiaoqian Jiang

The sparse factorization of a large matrix is fundamental in modern statistical learning. In particular, the sparse singular value decomposition and its variants have been utilized in multivariate regression, factor analysis, biclustering,…

Machine Learning · Statistics 2020-03-19 Kun Chen , Ruipeng Dong , Wanwan Xu , Zemin Zheng

Nearest neighbor is a popular class of classification methods with many desirable properties. For a large data set which cannot be loaded into the memory of a single machine due to computation, communication, privacy, or ownership…

Machine Learning · Statistics 2019-11-01 Xingye Qiao , Jiexin Duan , Guang Cheng

To analyse a very large data set containing lengthy variables, we adopt a sequential estimation idea and propose a parallel divide-and-conquer method. We conduct several conventional sequential estimation procedures separately, and properly…

Methodology · Statistics 2018-12-27 Zhanfeng Wang , Yuan-chin Ivan Chang

Generalized sparse matrix-matrix multiplication (or SpGEMM) is a key primitive for many high performance graph algorithms as well as for some linear solvers, such as algebraic multigrid. Here we show that SpGEMM also yields efficient…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-03-19 Aydin Buluc , John Gilbert

We propose a novel and efficient algorithm for the collaborative preference completion problem, which involves jointly estimating individualized rankings for a set of entities over a shared set of items, based on a limited number of…

Machine Learning · Statistics 2016-11-16 Suriya Gunasekar , Oluwasanmi Koyejo , Joydeep Ghosh

Lexicase selection is a semantic-aware parent selection method, which assesses individual test cases in a randomly-shuffled data stream. It has demonstrated success in multiple research areas including genetic programming, genetic…

Neural and Evolutionary Computing · Computer Science 2022-08-24 Li Ding , Ryan Boldi , Thomas Helmuth , Lee Spector

One of the biggest open problems in computational algebra is the design of efficient algorithms for Gr{\"o}bner basis computations that take into account the sparsity of the input polynomials. We can perform such computations in the case of…

Symbolic Computation · Computer Science 2018-06-22 Matías Bender , Jean-Charles Faugère , Elias Tsigaridas

Approval-Based Committee (ABC) rules are an important tool for choosing a fair set of candidates when given the preferences of a collection of voters. Though finding a winning committee for many ABC rules is NP-hard, natural variations for…

Computer Science and Game Theory · Computer Science 2025-08-06 Zack Fitzsimmons , Zohair Raza Hassan , Edith Hemaspaandra

This paper introduces a novel K-means clustering algorithm, an advancement on the conventional Big-means methodology. The proposed method efficiently integrates parallel processing, stochastic sampling, and competitive optimization to…

Machine Learning · Computer Science 2024-03-28 Rustam Mussabayev , Ravil Mussabayev

We demonstrate how efficiency of Cartesian Genetic Programming method can be scaled up through the preferential selection of phenotypically larger solutions, i.e. through the preferential selection of larger solutions among equally good…

Neural and Evolutionary Computing · Computer Science 2018-10-24 Nicola Milano , Stefano Nolfi

Studying the set of exact solutions of a system of polynomial equations largely depends on a single iterative algorithm, known as Buchberger's algorithm. Optimized versions of this algorithm are crucial for many computer algebra systems…

Machine Learning · Computer Science 2020-08-19 Dylan Peifer , Michael Stillman , Daniel Halpern-Leistner

To make a joint decision, agents (or voters) are often required to provide their preferences as linear orders. To determine a winner, the given linear orders can be aggregated according to a voting protocol. However, in realistic settings,…

Computational Complexity · Computer Science 2010-05-03 Nadja Betzler , Britta Dorn

The finite cell method is a highly flexible discretization technique for numerical analysis on domains with complex geometries. By using a non-boundary conforming computational domain that can be easily meshed, automatized computations on a…

Pioneered by Google's Pregel, many distributed systems have been developed for large-scale graph analytics. These systems expose the user-friendly "think like a vertex" programming interface to users, and exhibit good horizontal…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-01-26 Da Yan , James Cheng , M. Tamer Özsu , Fan Yang , Yi Lu , John C. S. Lui , Qizhen Zhang , Wilfred Ng

A method is given for quantitatively rating the social acceptance of different options which are the matter of a preferential vote. In contrast to a previous article, here the individual votes are allowed to be incomplete, that is, they…

Optimization and Control · Mathematics 2012-03-09 Rosa Camps , Xavier Mora , Laia Saumell

We study computational aspects of three prominent voting rules that use approval ballots to elect multiple winners. These rules are satisfaction approval voting, proportional approval voting, and reweighted approval voting. We first show…

Computer Science and Game Theory · Computer Science 2014-07-14 Haris Aziz , Serge Gaspers , Joachim Gudmundsson , Simon Mackenzie , Nicholas Mattei , Toby Walsh