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Subject selection plays a critical role in experimental studies, especially ones with human subjects. Anecdotal evidence suggests that many such studies, done at or near university campus settings suffer from selection bias, i.e., the…

Machine Learning · Computer Science 2020-12-21 Tahereh Arabghalizi , Alexandros Labrinidis

Higher educational institutions constantly look for ways to meet students' needs and support them through graduation. Recent work in the field of learning analytics have developed methods for grade prediction and course recommendations.…

Applications · Statistics 2019-06-12 Prableen Kaur , Agoritsa Polyzou , George Karypis

Despite the potential impact of explanations on decision making, there is a lack of research on quantifying their effect on users' choices. This paper presents an experimental protocol for measuring the degree to which positively or…

Human-Computer Interaction · Computer Science 2023-03-17 Krisztian Balog , Filip Radlinski , Andrey Petrov

With the recent implementation of the K to 12 Program, academic institutions, specifically, Colleges and Universities in the Philippines have been faced with difficulties in determining projected freshmen enrollees vis-a-vis decision-making…

Computers and Society · Computer Science 2024-09-05 Dr. Joseph A. Esquivel , James A. Esquivel

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

A family of models of individual discrete choice are constructed by means of statistical averaging of choices made by a subject in a reinforcement learning process, where the subject has short, k-term memory span. The choice probabilities…

Econometrics · Economics 2019-08-20 Misha Perepelitsa

We study the role of correlation in matching markets, where multiple decision-makers simultaneously face selection problems from the same pool of candidates. We propose a model in which a candidate's priority scores across different…

Computer Science and Game Theory · Computer Science 2025-12-08 Rémi Castera , Patrick Loiseau , Bary S. R. Pradelski

Imitation is a key component of human social behavior, and is widely used by both children and adults as a way to navigate uncertain or unfamiliar situations. But in an environment populated by multiple heterogeneous agents pursuing…

Neurons and Cognition · Quantitative Biology 2023-05-15 Max Taylor-Davies , Stephanie Droop , Christopher G. Lucas

University students routinely use the tools provided by online course ranking forums to share and discuss their satisfaction with the quality of instruction and content in a wide variety of courses. Student perception of the efficacy of…

Computers and Society · Computer Science 2019-07-15 Taha Hassan , Bob Edmison , Larry Cox , Matthew Louvet , Daron Williams

Designing recommendation systems that serve content aligned with time varying preferences requires proper accounting of the feedback effects of recommendations on human behavior and psychological condition. We argue that modeling the…

Information Retrieval · Computer Science 2022-08-09 Mihaela Curmei , Andreas Haupt , Dylan Hadfield-Menell , Benjamin Recht

Imagine a food recommender system -- how would we check if it is \emph{causing} and fostering unhealthy eating habits or merely reflecting users' interests? How much of a user's experience over time with a recommender is caused by the…

Machine Learning · Computer Science 2021-01-13 Sirui Yao , Yoni Halpern , Nithum Thain , Xuezhi Wang , Kang Lee , Flavien Prost , Ed H. Chi , Jilin Chen , Alex Beutel

We present a simple but effective method to measure and mitigate model biases caused by reliance on spurious cues. Instead of requiring costly changes to one's data or model training, our method better utilizes the data one already has by…

Computer Vision and Pattern Recognition · Computer Science 2023-11-01 Mazda Moayeri , Wenxiao Wang , Sahil Singla , Soheil Feizi

Machine learning models are routinely used to support decisions that affect individuals -- be it to screen a patient for a serious illness or to gauge their response to treatment. In these tasks, we are limited to learning models from…

Machine Learning · Computer Science 2025-06-10 Sujay Nagaraj , Yang Liu , Flavio P. Calmon , Berk Ustun

When inferring reward functions from human behavior (be it demonstrations, comparisons, physical corrections, or e-stops), it has proven useful to model the human as making noisy-rational choices, with a "rationality coefficient" capturing…

Machine Learning · Computer Science 2023-03-10 Gaurav R. Ghosal , Matthew Zurek , Daniel S. Brown , Anca D. Dragan

The ongoing rapid development of the e-commercial and interest-base websites make it more pressing to evaluate objects' accurate quality before recommendation by employing an effective reputation system. The objects' quality are often…

Physics and Society · Physics 2018-07-23 Leilei Wu , Zhuoming Ren , Xiao-Long Ren , Jianlin Zhang , Linyuan Lü

Imitation learning practitioners have often noted that conditioning policies on previous actions leads to a dramatic divergence between "held out" error and performance of the learner in situ. Interactive approaches can provably address…

Machine Learning · Computer Science 2021-02-12 Jonathan Spencer , Sanjiban Choudhury , Arun Venkatraman , Brian Ziebart , J. Andrew Bagnell

Strategic incentives may lead to inefficient and unequal provision of public services. A prominent example is school admissions. Existing research shows that applicants "play the system" by submitting school rankings strategically. We…

While academic metrics such as transcripts and GPA are commonly used to evaluate students' knowledge acquisition, there is a lack of comprehensive metrics to measure their preparedness for the challenges of post-graduation life. This…

Artificial Intelligence · Computer Science 2024-01-22 Izbassar Assylzhan , Muragul Muratbekova , Daniyar Amangeldi , Nazzere Oryngozha , Anna Ogorodova , Pakizar Shamoi

We consider the problem of designing affirmative action policies for selecting the top-k candidates from a pool of applicants. We assume that for each candidate we have socio-demographic attributes and a series of variables that serve as…

Computers and Society · Computer Science 2021-03-10 Michael Mathioudakis , Carlos Castillo , Giorgio Barnabo , Sergio Celis

We study a game theoretic model of standardized testing for college admissions. Students are of two types; High and Low. There is a college that would like to admit the High type students. Students take a potentially costly standardized…

Computer Science and Game Theory · Computer Science 2021-02-17 Sampath Kannan , Mingzi Niu , Aaron Roth , Rakesh Vohra
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