Results 71 to 80 of about 6,098 (213)
Digital Health, 2023 Objective This study aimed to examine the performance of machine learning models in predicting the progression of knee pain, functional decline, and incidence of knee osteoarthritis (OA) in high-risk individuals, with automated machine learning (AutoML ...
Tianrong Chen, Calvin Kalun Or
doaj +1 more source
Big Data in Cancer Genomics: Computational Foundations and Emerging Pathways for Precision Oncology
Computational and Systems Oncology, Volume 6, Issue 1, December 2026.ABSTRACT This review aims to explore the computational foundations of big data in cancer genomics and examine emerging pathways that support precision oncology and personalized cancer care. A narrative review approach was adopted to synthesize evidence from PubMed, Scopus, Web of Science, and IEEE Xplore.
Nur Vanu +8 more
wiley +1 more source
Reproducible AutoML: An Assessment of Research Reproducibility of No-Code AutoML Tools
Zusammenfassungen auf Deutsch und ...
Sabrina Pletzl +3 more
openaire +4 more sources
Journal of Geophysical Research: Atmospheres, Volume 131, Issue 21, 16 November 2026.Abstract Methane (CH4 ${\text{CH}}_{4}$) is a critical greenhouse gas, and accurate monitoring of its vertical distribution is essential for understanding its radiative impact and identifying emission sources. This paper introduces a novel methodology using a physics‐constrained neural network based on soft constraints to retrieve CH4 ${\text{CH}}_{4}$
Rocco Giosa +12 more
wiley +1 more source
Can AutoML outperform humans? An evaluation on popular OpenML datasets using AutoML Benchmark
, 2021 S.29-32In the last few years, Automated Machine Learning (AutoML) has gained much attention. With that said, the question arises whether AutoML can outperform results achieved by human data scientists.
Marc Hanussek +5 more
core +1 more source
Automated machine learning (AutoML) : case: predicting Formula One driver standings
, 2023 Tässä kandidaatintutkielmassa tutkittiin automatisoitua koneoppimista (AutoML) ja pyrittiin ennustamaan Formula 1 -osakilpailusijoituksia sen avulla. Tutkimuksessa perehdyttiin ensin koneoppimisen ja automatisoidun koneoppimisen teoriaan.
Laine, Renea
core +1 more source
How Automated Machine Learning Can Improve Business
Applied SciencesAutomated Machine Learning (AutoML) is revolutionizing how businesses utilize data, but there seems to be a lack of clarity and a holistic view regarding all its advantages, especially concerning the benefits of AutoML for companies.
Albérico Travassos Rosário +1 more
doaj +1 more source
SAMPLE-BASED DYNAMIC HIERARCHICAL TRANSFORMER WITH LAYER AND HEAD FLEXIBILITY VIA CONTEXTUAL BANDIT [PDF]
Proceedings on Engineering SciencesTransformer requires a fixed number of layers and heads which makes them inflexible to the complexity of individual samples and expensive in training and inference.
Fanfei Meng +3 more
doaj +1 more source
Carbon Neutralization, Volume 5, Issue 6, November 2026.The main purpose of this review is to summarize recent progress in the broad family of carbon‐based materials and their derivatives for CO2 capture. Rather than focusing on a single precursor or modification route, it examines pristine carbon adsorbents, functionalized carbon derivatives, and carbon‐based composites within a unified framework.
Jinliang Cai +4 more
wiley +1 more source
, 2020 The ChaLearn AutoML Challenge team conducted a large scale evaluation of fully automatic, black-box learning machines for feature-based classification and regression problems.
U Paris-Saclay +14 more
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