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Adapting machine learning algorithms to better handle the presence of clusters or batch effects within training datasets is important across a wide variety of biological applications. This article considers the effect of ensembling Random…

Machine Learning · Statistics 2025-04-01 Maya Ramchandran , Rajarshi Mukherjee , Giovanni Parmigiani

It is well known that different algorithms perform differently well on an instance of an algorithmic problem, motivating algorithm selection (AS): Given an instance of an algorithmic problem, which is the most suitable algorithm to solve…

Machine Learning · Computer Science 2022-11-01 Lukas Fehring , Jonas Hanselle , Alexander Tornede

Work zone safety is influenced by many risk factors. Consequently, a comprehensive knowledge of the risk factors identified from crash data analysis becomes critical in reducing risk levels and preventing severe crashes in work zones. This…

Computers and Society · Computer Science 2021-04-15 Huthaifa I Ashqar , Qadri H Shaheen , Suleiman A Ashur , Hesham A Rakha

Generating high-quality schedules for a rotating workforce is a critical task in all settings where a certain staffing level must be guaranteed beyond the capacity of single employees, such as for instance in industrial plants, hospitals,…

Other Computer Science · Computer Science 2011-11-09 Nysret Musliu , Johannes Gaertner , Wolfgang Slany

Many organizations depend on human decision-makers to make subjective decisions, especially in settings where information is scarce. Although workers are often viewed as interchangeable, the specific individual assigned to a task can…

Optimization and Control · Mathematics 2024-10-11 Eric G. Stratman , Justin J. Boutilier , Laura A. Albert

Forests play a crucial role in Earth's system processes and provide a suite of social and economic ecosystem services, but are significantly impacted by human activities, leading to a pronounced disruption of the equilibrium within…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Arthur Ouaknine , Teja Kattenborn , Etienne Laliberté , David Rolnick

The random forest (RF) algorithm has become a very popular prediction method for its great flexibility and promising accuracy. In RF, it is conventional to put equal weights on all the base learners (trees) to aggregate their predictions.…

Machine Learning · Statistics 2023-05-18 Xinyu Chen , Dalei Yu , Xinyu Zhang

The aim of this work is to present a meta-heuristically approach of the spatial assignment problem of human resources in multi-sites enterprise. Usually, this problem consists to move employees from one site to another based on one or more…

Artificial Intelligence · Computer Science 2013-11-01 Tkatek Said , Abdoun Otman , Abouchabaka Jaafar , Rafalia Najat

Next generation cellular networks will have to leverage large cell densifications to accomplish the ambitious goals for aggregate multi-user sum rates, for which CRAN architecture is a favored network design. This shifts the attention back…

Information Theory · Computer Science 2017-03-31 Sahar Imtiaz , Hadi Ghauch , Muhammad Mahboob Ur Rahman , George Koudouridis , James Gross

This paper investigates how software professionals perceive the economic implications of diversity in software engineering teams. Motivated by a gap in software engineering research, which has largely emphasized socio-technical and…

Software Engineering · Computer Science 2026-03-25 Sofia Tapias Montana , Ronnie de Souza Santos

As freelancing work keeps on growing almost everywhere due to a sharp decrease in communication costs and to the widespread of Internet-based labour marketplaces (e.g., guru.com, feelancer.com, mturk.com, upwork.com), many researchers and…

Computers and Society · Computer Science 2020-02-27 Giorgio Barnabò , Adriano Fazzone , Stefano Leonardi , Chris Schwiegelshohn

A central question for the future of work is whether person centered management can survive when algorithms take on managerial roles. Standard tools often miss what is happening because worker responses to algorithmic systems are rarely…

Machine Learning · Computer Science 2025-12-30 Arunkumar V , Nivethitha S , Sharan Srinivas , Gangadharan G. R

Data mining methods have been widely applied in financial markets, with the purpose of providing suitable tools for prices forecasting and automatic trading. Particularly, learning methods aim to identify patterns in time series and, based…

Machine Learning · Statistics 2013-01-22 Marcelo S. Lauretto , Barbara B. C. Silva , Pablo M. Andrade

Green data centers have become more and more popular recently due to their sustainability. The resource management module within a green data center, which is in charge of dispatching jobs and scheduling energy, becomes especially critical…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-09-15 Huangxin Wang , Jean X. Zhang , Bo Yang , Fei Li

Random forest regression (RF) is an extremely popular tool for the analysis of high-dimensional data. Nonetheless, its benefits may be lessened in sparse settings due to weak predictors, and a pre-estimation dimension reduction (targeting)…

Random forest (RF) methodology is one of the most popular machine learning techniques for prediction problems. In this article, we discuss some cases where random forests may suffer and propose a novel generalized RF method, namely…

Machine Learning · Statistics 2019-04-24 Haozhe Zhang , Dan Nettleton , Zhengyuan Zhu

Information technology (IT) organizations are increasing the use of agile practices, which are based on a people-centred culture alongside the software development process. Thus, it is vital to understand the social and human factors of the…

Software Engineering · Computer Science 2020-06-08 Luís Felipe Amorim , Marcelo Marinho , Suzana Sampaio

Recruiters usually spend less than a minute looking at each r\'esum\'e when deciding whether it's worth continuing the recruitment process with the candidate. Recruiters focus on keywords, and it's almost impossible to guarantee a fair…

Computation and Language · Computer Science 2016-06-23 Tim Zimmermann , Leo Kotschenreuther , Karsten Schmidt

As automatic optimization techniques find their way into industrial applications, the behavior of many complex systems is determined by some form of planner picking the right actions to optimize a given objective function. In many cases,…

Neural and Evolutionary Computing · Computer Science 2018-10-31 Thomas Gabor , Lenz Belzner , Thomy Phan , Kyrill Schmid

Widespread developments in automation have reduced the need for human input. However, despite the increased power of machine learning, in many contexts these programs make decisions that are problematic. Biases within data and opaque models…

Human-Computer Interaction · Computer Science 2020-04-16 Max Langenkamp , Allan Costa , Chris Cheung
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