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Crowdsourcing has been successfully employed in the past as an effective and cheap way to execute classification tasks and has therefore attracted the attention of the research community. However, we still lack a theoretical understanding…

Human-Computer Interaction · Computer Science 2016-10-20 Edoardo Manino , Long Tran-Thanh , Nicholas R. Jennings

When eliciting judgements from humans for an unknown quantity, one often has the choice of making direct-scoring (cardinal) or comparative (ordinal) measurements. In this paper we study the relative merits of either choice, providing…

The moral foundations theory supports that people, across cultures, tend to consider a small number of dimensions when classifying issues on a moral basis. The data also show that the statistics of weights attributed to each moral dimension…

Physics and Society · Physics 2014-03-25 Renato Vicente , Alex Susemihl , João Pedro Jericó , Nestor Caticha

When users rate objects, a sophisticated algorithm that takes into account ability or reputation may produce a fairer or more accurate aggregation of ratings than the straightforward arithmetic average. Recently a number of authors have…

Information Retrieval · Computer Science 2015-03-13 Matus Medo , Joseph Rushton Wakeling

We consider the issue of strategic behaviour in various peer-assessment tasks, including peer grading of exams or homeworks and peer review in hiring or promotions. When a peer-assessment task is competitive (e.g., when students are graded…

Multiagent Systems · Computer Science 2020-10-09 Ivan Stelmakh , Nihar B. Shah , Aarti Singh

Machine Learning models have many potentially beneficial applications in education settings, but a key barrier to their development is securing enough data to train these models. Labelling educational data has traditionally relied on highly…

Computation and Language · Computer Science 2023-11-10 Owen Henkel , Libby Hills

We investigate the mechanism design problem faced by a principal who hires \emph{multiple} agents to gather and report costly information. Then, the principal exploits the information to make an informed decision. We model this problem as a…

Computer Science and Game Theory · Computer Science 2023-07-13 Federico Cacciamani , Matteo Castiglioni , Nicola Gatti

Offline policy evaluation (OPE) allows us to evaluate and estimate a new sequential decision-making policy's performance by leveraging historical interaction data collected from other policies. Evaluating a new policy online without a…

Machine Learning · Computer Science 2024-11-04 Allen Nie , Yash Chandak , Christina J. Yuan , Anirudhan Badrinath , Yannis Flet-Berliac , Emma Brunskil

The objective of ordinal embedding is to find a Euclidean representation of a set of abstract items, using only answers to triplet comparisons of the form "Is item $i$ closer to the item $j$ or item $k$?". In recent years, numerous…

Machine Learning · Computer Science 2021-10-22 Leena Chennuru Vankadara , Siavash Haghiri , Michael Lohaus , Faiz Ul Wahab , Ulrike von Luxburg

Crowdsourcing is now widely used to replace judgement by an expert authority with an aggregate evaluation from a number of non-experts, in applications ranging from rating and categorizing online content to evaluation of student assignments…

Computer Science and Game Theory · Computer Science 2013-03-05 Anirban Dasgupta , Arpita Ghosh

Off-policy evaluation (OPE) is to evaluate a target policy with data generated by other policies. Most previous OPE methods focus on precisely estimating the true performance of a policy. We observe that in many applications, (1) the end…

Machine Learning · Computer Science 2022-06-22 Yue Jin , Yue Zhang , Tao Qin , Xudong Zhang , Jian Yuan , Houqiang Li , Tie-Yan Liu

The label ranking problem is a supervised learning scenario in which the learner predicts a total order of the class labels for a given input instance. Recently, research has increasingly focused on the partial label ranking problem, a…

Machine Learning · Computer Science 2025-10-24 Jiayi Wang , Juan C. Alfaro , Viktor Bengs

We propose an innovative statistical method, called Ordinal Mixed-Effect Random Forest (OMERF), that extends the use of random forest to the analysis of hierarchical data and ordinal responses. The model preserves the flexibility and…

Methodology · Statistics 2024-06-06 Giulia Bergonzoli , Lidia Rossi , Chiara Masci

Online Judge (OJ) systems are typically considered within programming-related courses as they yield fast and objective assessments of the code developed by the students. Such an evaluation generally provides a single decision based on a…

Computers and Society · Computer Science 2024-02-07 Juan Ramón Rico-Juan , Víctor M. Sánchez-Cartagena , Jose J. Valero-Mas , Antonio Javier Gallego

Consider designing an effective crowdsourcing system for an $M$-ary classification task. Crowd workers complete simple binary microtasks whose results are aggregated to give the final result. We consider the novel scenario where workers…

Machine Learning · Computer Science 2016-12-14 Qunwei Li , Aditya Vempaty , Lav R. Varshney , Pramod K. Varshney

This paper studies the distributed optimization problem over directed networks with noisy information-sharing. To resolve the imperfect communication issue over directed networks, a series of noise-robust variants of Push-Pull/AB method…

Optimization and Control · Mathematics 2023-07-28 Shengchao Zhao , Siyuan Song , Yongchao Liu

This study aims to investigate whether GPT-4 can effectively grade assignments for design university students and provide useful feedback. In design education, assignments do not have a single correct answer and often involve solving an…

Artificial Intelligence · Computer Science 2024-09-27 Qian Huang , Thijs Willems , King Wang Poon

Active learning strategies have been widely recognised for their effectiveness in tertiary education, yet their implementation at scale, particularly in large first-year mathematics courses, presents considerable challenges. A common method…

History and Overview · Mathematics 2025-04-30 Raymond Vozzo , Stuart Johnson , Jonathan Tuke , Tanya Evans

In the peer selection problem a group of agents must select a subset of themselves as winners for, e.g., peer-reviewed grants or prizes. Here, we take a Condorcet view of this aggregation problem, i.e., that there is a ground-truth ordering…

Computer Science and Game Theory · Computer Science 2021-07-22 Omer Lev , Nicholas Mattei , Paolo Turrini , Stanislav Zhydkov

Reaching some form of consensus is often necessary for autonomous agents that want to coordinate their actions or otherwise engage in joint activities. One way to reach a consensus is by aggregating individual information, such as…

Multiagent Systems · Computer Science 2016-07-13 Marija Slavkovik