Related papers: Open Access Policy: Numbers, Analysis, Effectivene…
Open-source software (OSS) is a pillar of modern software development. Its success depends on the dedication of maintainers who work constantly to keep their libraries stable, adapt to changing needs, and support a growing community. Yet,…
Open Learning Analytics (OLA) is an emerging research area that aims at improving learning efficiency and effectiveness in lifelong learning environments. OLA employs multiple methods to draw value from a wide range of educational data…
Decisions impacting human lives are increasingly being made or assisted by automated decision-making algorithms. Many of these algorithms process personal data for predicting recidivism, credit risk analysis, identifying individuals using…
Open-world machine learning (ML) combines closed-world models trained on in-distribution data with out-of-distribution (OOD) detectors, which aim to detect and reject OOD inputs. Previous works on open-world ML systems usually fail to test…
Age of information (AoI), defined as the time elapsed since the last received update was generated, is a newly proposed metric to measure the timeliness of information updates in a network. We consider AoI minimization problem for a network…
Determination of the correct mix of dividend and retained earnings and its effect on profitability has been a subject of controversy in financial management literature. This paper seeks to contribute to the ongoing debate by examining the…
Open Educational Resources (OERs) are openly licensed educational materials that are widely used for learning. Nowadays, many online learning repositories provide millions of OERs. Therefore, it is exceedingly difficult for learners to find…
Aggregations of Web resources are increasingly important in scholarship as it adopts new methods that are data-centric, collaborative, and networked-based. The same notion of aggregations of resources is common to the mashed-up, socially…
Quantifying the impact of scientific papers objectively is crucial for research output assessment, which subsequently affects institution and country rankings, research funding allocations, academic recruitment and national/international…
Evaluating policies using off-policy data is crucial for applying reinforcement learning to real-world problems such as healthcare and autonomous driving. Previous methods for off-policy evaluation (OPE) generally suffer from high variance…
Massive Open Online Courseware (MOOCs) appeared in 2008 and grew considerably in the past decade, now reaching millions of students and professionals all over the world. MOOCs do not replace other educational forms. Instead, they complement…
This paper reviews research literature on Diamond Open Access (DOA) journals - sometimes also called Platinum Open Access - that was produced after this journal segment started to become a priority in European research policy around 2020.…
We explicitly test if the reliability of credit ratings depends on the total number of admissible states. We analyse open access credit rating data and show that the effect of the number of states in the dynamical properties of ratings…
Many real-world resource allocation systems, such as humanitarian logistics and vaccine distribution, must preposition limited supply across multiple locations before demand is realized while stockouts incur irreversible service losses. To…
Many studies have now reported the positive correlation between Open Access (OA) self-archiving and citation counts ("OA Advantage," OAA). But does this OAA occur because (QB) authors are more likely to self-selectively self-archive…
Off-policy evaluation methods are important in recommendation systems and search engines, where data collected under an existing logging policy is used to estimate the performance of a new proposed policy. A common approach to this problem…
We revisit the problem of offline reinforcement learning with value function realizability but without Bellman completeness. Previous work by Xie and Jiang (2021) and Foster et al. (2022) left open the question whether a bounded…
Context: Open public data enable different stakeholders to perform analysis and uncover information from different perspectives. The identification and analysis of data from prison systems is not a trivial task. It raises the need for the…
We investigate how different preservation policies ranging from least aggressive to Most aggressive affect the level of preservation achieved by autonomic processes used by smart digital objects (DOs). The mechanisms used to support…
The use of recommender systems in the recruitment domain has been labeled as 'high-risk' in recent legislation. As a result, strict requirements regarding explainability and fairness have been put in place to ensure proper treatment of all…