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Related papers: Sorting and Grading

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Scoring systems, as a type of predictive model, have significant advantages in interpretability and transparency and facilitate quick decision-making. As such, scoring systems have been extensively used in a wide variety of industries such…

Machine Learning · Computer Science 2022-11-23 Yi Yang , Ying Wu , Mei Li , Xiangyu Chang , Yong Tan

In management education programmes today, students face a difficult time in choosing electives as the number of electives available are many. As the range and diversity of different elective courses available for selection have increased,…

Information Retrieval · Computer Science 2013-09-27 Sanjog Ray , Anuj Sharma

Algorithmic decision making systems are ubiquitous across a wide variety of online as well as offline services. These systems rely on complex learning methods and vast amounts of data to optimize the service functionality, satisfaction of…

Machine Learning · Statistics 2017-03-27 Muhammad Bilal Zafar , Isabel Valera , Manuel Gomez Rodriguez , Krishna P. Gummadi

The problem of ranking/ordering instances, instead of simply classifying them, has recently gained much attention in machine learning. In this paper we formulate the ranking problem in a rigorous statistical framework. The goal is to learn…

Statistics Theory · Mathematics 2016-08-16 Stéphan Clémençon , Gábor Lugosi , Nicolas Vayatis

Scoring rules are widely used to rank athletes in sports and candidates in elections. Each position in each individual ranking is worth a certain number of points; the total sum of points determines the aggregate ranking. The question is…

Computer Science and Game Theory · Computer Science 2022-09-09 Aleksei Y. Kondratev , Egor Ianovski , Alexander S. Nesterov

The learning-to-rank problem aims at ranking items to maximize exposure of those most relevant to a user query. A desirable property of such ranking systems is to guarantee some notion of fairness among specified item groups. While fairness…

Machine Learning · Computer Science 2021-11-23 James Kotary , Ferdinando Fioretto , Pascal Van Hentenryck , Ziwei Zhu

Many U.S. colleges now use test-optional admissions. A frequent claim is that by not seeing standardized test scores, a college can admit a student body it prefers, say with more diversity. But how can observing less information improve…

Theoretical Economics · Economics 2024-11-12 Wouter Dessein , Alex Frankel , Navin Kartik

People are rated and ranked, towards algorithmic decision making in an increasing number of applications, typically based on machine learning. Research on how to incorporate fairness into such tasks has prevalently pursued the paradigm of…

Machine Learning · Computer Science 2019-02-07 Preethi Lahoti , Krishna P. Gummadi , Gerhard Weikum

This chapter surveys the application of matching theory to school choice, motivated by the shift from neighborhood assignment systems to choice-based models. Since educational choice is not mediated by price, the design of allocation…

General Economics · Economics 2025-12-24 Yeon-Koo Che , Julien Grenet , Yinghua He

Peer grading has emerged as a scalable solution for assessment in large and online classrooms, offering both logistical efficiency and pedagogical value. However, designing effective peer-grading systems remains challenging due to…

Computers and Society · Computer Science 2025-12-02 Uchswas Paul , Ananya Mantravadi , Jash Shah , Shail Shah , Sri Vaishnavi Mylavarapu , M Parvez Rashid , Edward Gehringer

Curriculum learning is a training strategy that sorts the training examples by some measure of their difficulty and gradually exposes them to the learner to improve the network performance. Motivated by our insights from implicit curriculum…

Machine Learning · Computer Science 2021-07-28 Vinu Sankar Sadasivan , Anirban Dasgupta

We study the role of information and access in capacity-constrained selection problems with fairness concerns. We develop a statistical discrimination framework, where each applicant has multiple features and is potentially strategic. The…

Computers and Society · Computer Science 2026-03-03 Nikhil Garg , Hannah Li , Faidra Monachou

Prevailing methods of course allocation at undergraduate institutions involve reserving seats to give priority to designated groups of students. We introduce a competitive equilibrium-based mechanism that assigns course seats using student…

Theoretical Economics · Economics 2025-12-24 Daniel Kornbluth , Alexey Kushnir

A vast majority of the school choice literature focuses on designing mechanisms to simultaneously assign students to many schools, and employs a "make it up as you go along" approach when it comes to each school's admissions policy. An…

Theoretical Economics · Economics 2021-04-20 Battal Dogan

High school and college graduates seemingly are often battling for the courses they should major in order to achieve their target career. In this paper, we worked on suggesting a career path to a graduate to reach his/her dream career given…

Computers and Society · Computer Science 2015-10-20 Akshay Nagpal , Supriya P. Panda

We introduce a novel re-ranking model that aims to augment the functionality of standard search engines to support classroom search activities for children (ages 6 to 11). This model extends the known listwise learning-to-rank framework by…

Information Retrieval · Computer Science 2023-08-30 Garrett Allen , Katherine Landau Wright , Jerry Alan Fails , Casey Kennington , Maria Soledad Pera

Public and private institutions must often allocate scare resources under uncertainty. Banks, for example, extend credit to loan applicants based in part on their estimated likelihood of repaying a loan. But when the quality of information…

Computers and Society · Computer Science 2021-10-11 William Cai , Johann Gaebler , Nikhil Garg , Sharad Goel

Public school districts across the United States have implemented school choice systems that have the potential to improve underserved students' access to educational opportunities. However, research has shown that learning about and…

Human-Computer Interaction · Computer Science 2022-04-01 Samantha Robertson , Tonya Nguyen , Niloufar Salehi

This paper proposes a stylized, dynamic model to address the issue of sorting online. There are two large homogeneous groups of individuals. Everyone must choose between two online platforms, one of which has superior amenities (akin to…

General Economics · Economics 2024-05-21 John Lynham , Philip R. Neary

It is common to evaluate a set of items by soliciting people to rate them. For example, universities ask students to rate the teaching quality of their instructors, and conference organizers ask authors of submissions to evaluate the…

Machine Learning · Statistics 2020-12-02 Jingyan Wang , Ivan Stelmakh , Yuting Wei , Nihar B. Shah