Results 51 to 60 of about 1,371,617 (304)
Gap between theory and practice: noise sensitive word alignment in machine translation [PDF]
, 2010 Word alignment is to estimate a lexical translation probability p(e|f), or to estimate the correspondence g(e, f) where a function g outputs either 0 or 1, between a source word f and a target word e for given bilingual sentences.
Okita, Tsuyoshi +2 more
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Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Cognitive impairment is a common non‐motor symptom in Multiple Sclerosis (MS), negatively affecting autonomy and Quality of Life (QoL). Innovative rehabilitation strategies, such as semi‐immersive virtual reality (VR) and computerized cognitive training (CCT), may offer advantages over traditional cognitive rehabilitation (TCR ...
Maria Grazia Maggio +8 more
wiley +1 more source
Learning Rate Adaptation for Differentially Private Learning [PDF]
, 2020 Peer ...
Koskela, Antti, Honkela, Antti
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Machine Learning and Statistics: A Study for assessing innovative Demand Forecasting Models
IEEE International Symposium on Multimedia, 2020 Besides increasing dynamics in market demands, companies strive to avoid short-term changes in their supply chain planning. Therefore, an essential lever to improve supply chain performance is the optimization of the demand forecast.
N. Moroff, E. Kurt, J. Kamphues
semanticscholar +1 more source
Screening Routine Clinical Notes for Epilepsy Surgery Candidates Using Large Language Models
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Epilepsy surgery is severely underutilized despite proven efficacy, with substantial under‐referral of eligible patients in routine clinical practice. This study evaluated the potential role of large language models (LLMs) as decision‐support tools for screening unstructured clinical notes to identify epilepsy surgery candidates and ...
Uriel Fennig +9 more
wiley +1 more source
, 2013 We examine the performance of an ensemble of randomly-projected Fisher Linear Discriminant classifiers, focusing on the case when there are fewer training observations than data dimensions.
Kabán, Ata, Durrant, Robert J.
core +1 more source
, 2020 This mixed research aims to analysis and design the Web Game On Descriptive Statistics (WGODS) through the ADDIE model, data science and machine learning. The sample consists of 61 students from a university in Mexico. WGODS is a technological tool (quiz
R. Salas-Rueda +2 more
semanticscholar +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Facioscapulohumeral muscular dystrophy (FSHD) is one of the most debilitating and common muscular dystrophies. Despite its severity, no approved therapy exists for FSHD patients. However, several therapeutic candidates are currently under development, and some have recently entered clinical trials, marking the need for reliable ...
Mustafa Bilal Bayazit +11 more
wiley +1 more source
A machine learning model that outperforms conventional global subseasonal forecast models
Nature CommunicationsSkillful subseasonal forecasts are crucial for various sectors of society but pose a grand scientific challenge. Recently, machine learning-based weather forecasting models outperform the most successful numerical weather predictions generated by the ...
Lei Chen +11 more
semanticscholar +1 more source
Uncovering G Protein‐Coupled Receptors: Novel Targets and Biomarkers for Predicting Glioma Prognosis
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Low‐grade gliomas (LGG) exhibit significant heterogeneity and recurrence risk. G protein‐coupled receptors (GPCR) contribute to glioma malignant progression, but their prognostic value remains unclear. This work attempts to formulate a GPCR‐based outcome‐predicting model for LGG. Methods Based on TCGA LGG data, the enrichment scores
Jun Yang +4 more
wiley +1 more source