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We consider the optimal value of information (VoI) problem, where the goal is to sequentially select a set of tests with a minimal cost, so that one can efficiently make the best decision based on the observed outcomes. Existing algorithms…

Artificial Intelligence · Computer Science 2017-07-18 Yuxin Chen , Jean-Michel Renders , Morteza Haghir Chehreghani , Andreas Krause

As conventional answer selection (AS) methods generally match the question with each candidate answer independently, they suffer from the lack of matching information between the question and the candidate. To address this problem, we…

Computation and Language · Computer Science 2020-10-13 Yingxue Zhang , Fandong Meng , Peng Li , Ping Jian , Jie Zhou

Automated short answer grading (ASAG) with large language models (LLMs) is commonly evaluated with aggregate metrics such as macro-F1 and Cohen's kappa. However, these metrics provide limited insight into how grading performance varies…

Computation and Language · Computer Science 2026-05-14 Longwei Cong , Sonja Hahn , Sebastian Gombert , Leon Camus , Hendrik Drachsler , Ulf Kroehne

Accurate and reliable prediction of hospital admission location is important due to resource-constraints and space availability in a clinical setting, particularly when dealing with patients who come from the emergency department. In this…

Machine Learning · Computer Science 2020-07-07 Rasheed el-Bouri , David Eyre , Peter Watkinson , Tingting Zhu , David Clifton

The item response theory obtains the estimates and their confidence intervals for parameters of abilities of examinees and difficulties of problems by using the observed item response matrix consisting of 0/1 value elements. Many papers…

Computation · Statistics 2022-03-08 Hideo Hirose

Background: In medical and health professions education (HPE), AI is increasingly used to assess clinical competencies, including via virtual standardized patients. However, most evaluations rely on AI-human interrater reliability and lack…

We introduce a new model for online ranking in which the click probability factors into an examination and attractiveness function and the attractiveness function is a linear function of a feature vector and an unknown parameter. Only…

Machine Learning · Statistics 2019-05-28 Shuai Li , Tor Lattimore , Csaba Szepesvári

This study presents a theoretical analysis on the efficiency of interleaving, an efficient online evaluation method for rankings. Although interleaving has already been applied to production systems, the source of its high efficiency has…

Information Retrieval · Computer Science 2023-06-21 Kojiro Iizuka , Hajime Morita , Makoto P. Kato

Successful teaching requires an assumption of how the learner learns - how the learner uses experiences from the world to update their internal states. We investigate what expectations people have about a learner when they teach them in an…

Machine Learning · Computer Science 2023-06-30 Yun-Shiuan Chuang , Xuezhou Zhang , Yuzhe Ma , Mark K. Ho , Joseph L. Austerweil , Xiaojin Zhu

Humans can progressively learn visual concepts from easy to hard questions. To mimic this efficient learning ability, we propose a competence-aware curriculum for visual concept learning in a question-answering manner. Specifically, we…

Computer Vision and Pattern Recognition · Computer Science 2020-07-29 Qing Li , Siyuan Huang , Yining Hong , Song-Chun Zhu

Curriculum learning--ordering training examples in a sequence to aid machine learning--takes inspiration from human learning, but has not gained widespread acceptance. Static strategies for scoring item difficulty rely on indirect proxy…

Machine Learning · Computer Science 2026-03-17 Zhenwei Tang , Amogh Inamdar , Ashton Anderson , Richard Zemel

This paper aims to determine how the LMS Web portal application reshapes the learner experience through the developed E-Learning Management System using Data Mining Algorithm. The methodology that the researchers used is descriptive…

Computers and Society · Computer Science 2023-09-25 Cecilia P. Abaricia , Manuel Luis C. Delos Santos

Consider a storage area where arriving items are stored temporarily in bounded capacity stacks until their departure. We look into the problem of deciding where to put an arriving item with the objective of minimizing the maximum number of…

Data Structures and Algorithms · Computer Science 2020-06-11 Martin Olsen , Allan Gross

We consider the problem of online multiclass classification with partial feedback, where an algorithm predicts a class for a new instance in each round and only receives its correctness. Although several methods have been developed for this…

Machine Learning · Computer Science 2019-02-05 Takuo Kaneko , Issei Sato , Masashi Sugiyama

In today\^as world designing adaptable course material requires new technical knowledge which involves a need for a uniform protocol that allows organizing resources with emphasis on quality and Learning. This can be achieved by bundling…

Computers and Society · Computer Science 2010-07-27 Sonal Chawla , R. K. Singla

Research is described on a system for web-assisted education and how it is used to deliver on-line drill questions, automatically suited to individual students. The system can store and display all of the various pieces of information used…

Physics Education · Physics 2014-06-27 Anna Helga Jonsdottir , Gunnar Stefansson

A freely available educational application (a mobile website) is presented. This provides access to educational material and drilling on selected topics within mathematics and statistics with an emphasis on tablets and mobile phones. The…

Other Statistics · Statistics 2014-12-10 Jamie Lentin , Anna H. Jonsdottir , David Stern , Victoria Mokua , Gunnar Stefansson

Grading of examination papers is a hectic, time-labor intensive task and is often subjected to inefficiency and bias in checking. This research project is a primitive experiment in the automation of grading of theoretical answers written in…

Machine Learning · Computer Science 2020-04-21 Rahul Kr Chauhan , Ravinder Saharan , Siddhartha Singh , Priti Sharma

Large language models (LLMs) achieve high performance on mathematical reasoning, but these results can be inflated by training data leakage or superficial pattern matching rather than genuine reasoning. To this end, an adversarial…

Computation and Language · Computer Science 2026-02-03 Xinyuan Li , Murong Xu , Wenbiao Tao , Hanlun Zhu , Yike Zhao , Jipeng Zhang , Yunshi Lan

Imagine a large firm with multiple departments that plans a large recruitment. Candidates arrive one-by-one, and for each candidate the firm decides, based on her data (CV, skills, experience, etc), whether to summon her for an interview.…

Machine Learning · Computer Science 2019-06-03 Alon Cohen , Avinatan Hassidim , Haim Kaplan , Yishay Mansour , Shay Moran
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