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Academic Articles & Research Papers
Showing 20 of 926 academic articles
Maria Schuld, Ilya Sinayskiy, Francesco Petruccione • Contemporary Physics
(2014)
Machine learning algorithms learn a desired input-output relation from examples in order to interpret new inputs. This is important for tasks such as image and speech recognition or strategy optimisation, with growing applications in the IT...
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Open Access
DOI: https://doi.org/10.1080/00107514.2014.964942
Joost Verbraeken, Matthijs Wolting, Jonathan Katzy, Jeroen Kloppenburg et al. • ACM Computing Surveys
(2020)
The demand for artificial intelligence has grown significantly over the past decade, and this growth has been fueled by advances in machine learning techniques and the ability to leverage hardware acceleration. However, to increase the qual...
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Open Access
DOI: https://doi.org/10.1145/3377454
Marieth Agnes Guillen-García, Osnamir Elias Bru-Cordero, Cristian David Correa-Álvarez • Big Data and Cognitive Computing
(2026)
Student retention analytics often treats withdrawal as a single outcome, although students may attribute dropout intention to personal, socioeconomic, and academic pressures simultaneously. We benchmarked nine supervised classifiers for ide...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/bdcc10080274
Maher Abuhussain, Ali Hussain Alhamami, Khaled Almazam, Omar Humaidan et al. • Buildings
(2025)
This study introduces a comprehensive framework combining building information modeling (BIM), project management body of knowledge (PMBOK), and machine learning (ML) to optimize energy efficiency and reduce environmental impacts in Riyadh’...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/buildings15173031
Simon Rogers, Mark Girolami • Chapman & Hall/CRC eBooks
(2016)
"A First Course in Machine Learning by Simon Rogers and Mark Girolami is the best introductory book for ML currently available. It combines rigor and precision with accessibility, starts from a detailed explanation of the basic foundations ...
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DOI: https://doi.org/10.1201/9781315382159
Konstantinos G. Liakos, Patrizia Busato, Dimitrios Moshou, Simon Pearson et al. • Sensors
(2018)
Machine learning has emerged with big data technologies and high-performance computing to create new opportunities for data intensive science in the multi-disciplinary agri-technologies domain. In this paper, we present a comprehensive revi...
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cc-by
DOI: https://doi.org/10.3390/s18082674
PMC: 6111295
Jerry Alan Fails, Dan R. Olsen • ACM International Conference on Intelligent User Interfaces (IUI)
(2003)
Perceptual user interfaces (PUIs) are an important part of ubiquitous computing. Creating such interfaces is difficult because of the image and signal processing knowledge required for creating classifiers. We propose an interactive machine...
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DOI: https://doi.org/10.1145/604045.604056
Ji-Hoon Kim, Seunghee Han, Kwanghyun Park, Soo-Young Ji et al. • IEEE Access
(2024)
The ability to perform machine learning (ML) tasks in a database management system (DBMS) is a new paradigm for conventional database systems as it enables advanced data analytics on top of well-established capabilities of DBMSs. However, t...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2023.3347725
Sridhar Chandrasekaran, Yao-Feng Chang, Firman Mangasa Simanjuntak • Nanomaterials
(2026)
The memristor has long been known as a nonvolatile memory technology alternative and has recently been explored for neuromorphic computing, owing to its capability to mimic the synaptic plasticity of the human brain. The architecture of a m...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/nano16030179
Dhurgham Ali Mohammed, Kalyani A. Patel • ICTACT Journal on Soft Computing
(2025)
In text sentiment analysis, a crucial challenge is that conventional word vectors fail to capture lexical ambiguity. The Gated Recurrent Unit (GRU), an advanced variant of RNN, is extensively utilized in natural language processing tasks su...
DOAJ
Open Access (DOAJ)
DOI: 10.21917/ijsc.2025.0518
Dana Pessach, Erez Shmueli • ACM Computing Surveys
(2022)
An increasing number of decisions regarding the daily lives of human beings are being controlled by artificial intelligence and machine learning (ML) algorithms in spheres ranging from healthcare, transportation, and education to college ad...
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DOI: https://doi.org/10.1145/3494672
Hyuk Lee • Applied Sciences
(2025)
As edge computing environments become increasingly dynamic, the need for efficient job scheduling and proactive fault prevention is becoming paramount. In such environments, minimizing machine downtime and maintaining productivity are criti...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app15041771
Hilal M. El Misilmani, Tarek Naous • International Conference on High Performance Computing & Simulation (HPCS)
(2019)
With the growth and wide variety of available data, advanced processing, and affordable data storage, machine learning is witnessing great attention in finding optimized solutions in various fields. Machine learning techniques are currently...
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DOI: https://doi.org/10.1109/hpcs48598.2019.9188224
El‐Ghazali Talbi • ACM Computing Surveys
(2021)
During the past few years, research in applying machine learning (ML) to design efficient, effective, and robust metaheuristics has become increasingly popular. Many of those machine learning-supported metaheuristics have generated high-qua...
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Open Access
DOI: https://doi.org/10.1145/3459664
Adi Laurentiu Tarca, Vincent J. Carey, Xuewen Chen, Roberto J. Romero et al. • PLoS Computational Biology
(2007)
The term machine learning refers to a set of topics dealing with the creation and evaluation of algorithms that facilitate pattern recognition, classification, and prediction, based on models derived from existing data. Two facets of mechan...
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public-domain
DOI: https://doi.org/10.1371/journal.pcbi.0030116
PMC: 1904382
Zhixin Lu, Brian R. Hunt, Edward Ott • Chaos An Interdisciplinary Journal of Nonlinear Science
(2018)
A machine-learning approach called "reservoir computing" has been used successfully for short-term prediction and attractor reconstruction of chaotic dynamical systems from time series data. We present a theoretical framework that describes...
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Open Access
DOI: https://doi.org/10.1063/1.5039508
Sebastian Raschka, Joshua M. Patterson, Corey Nolet • Information
(2020)
Smarter applications are making better use of the insights gleaned from data, having an impact on every industry and research discipline. At the core of this revolution lies the tools and the methods that are driving it, from processing the...
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cc-by
DOI: https://doi.org/10.3390/info11040193
Naga Ramesh Palakurti, Nageswararao Kanchepu • Advances in systems analysis, software engineering, and high performance computing book series
(2024)
This chapter delves into the core principles of machine learning, offering practical insights for effective data processing. From foundational concepts to advanced techniques, the narrative unfolds as a comprehensive guide for harnessing th...
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DOI: https://doi.org/10.4018/979-8-3693-2909-2.ch002
Sarah J. MacEachern, Nils D. Forkert • Genome
(2020)
Precision medicine is an emerging approach to clinical research and patient care that focuses on understanding and treating disease by integrating multi-modal or multi-omics data from an individual to make patient-tailored decisions. With t...
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Open Access
DOI: https://doi.org/10.1139/gen-2020-0131
Fabrizio Sebastiani • ACM Computing Surveys
(2002)
The automated categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last 10 years, due to the increased availability of documents in digital form and the ensuing need to organize them...
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Open Access
DOI: https://doi.org/10.1145/505282.505283