Results 121 to 130 of about 1,259,133 (314)
Blockwise Self-Supervised Learning at Scale [PDF]
Publisher Copyright: © 2024, Transactions on Machine Learning Research. All rights reserved.Current state-of-the-art deep networks are all powered by backpropagation.
Lecun, Yann +3 more
core
Beyond multi-class – structured learning for machine translation [PDF]
, 2010 In this thesis, we explore and present machine learning (ML) approaches to a particularly challenging research area – machine translation (MT). The study aims at replacing or developing each component in the MT system with an appropriate discriminative ...
Ni, Y, Ni, Yizhao
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Adaptive Robust Learning using Latent Bernoulli Variables [PDF]
We present an adaptive approach for robust learning from corrupted training sets. We identify corrupted and non-corrupted samples with latent Bernoulli variables and thus formulate the learning problem as maximization of the likelihood where latent ...
Karakulev, Aleksandr +2 more
core +2 more sources
3D scattering transforms for disease classification in neuroimaging
NeuroImage: Clinical, 2017 Classifying neurodegenerative brain diseases in MRI aims at correctly assigning discrete labels to MRI scans. Such labels usually refer to a diagnostic decision a learner infers based on what it has learned from a training sample of MRI scans ...
Tameem Adel +3 more
doaj +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
A Two‐Stage Questionnaire and Actigraphy Screening for iRBD in a Multicenter Retrospective Cohort
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Isolated rapid‐eye‐movement sleep behavior disorder is a prodromal marker of synucleinopathies. However, most cases remain undiagnosed due to the insufficient predictive value of questionnaires and limited access to confirmatory video‐polysomnography. We assessed a two‐stage screening strategy combining a brief questionnaire on rapid‐
Caleb A. Massimi +17 more
wiley +1 more source
Machine Learning Did Not Outperform Conventional Competing Risk Modeling to Predict Revision Arthroplasty [PDF]
BACKGROUND: Estimating the risk of revision after arthroplasty could inform patient and surgeon decision-making. However, there is a lack of well-performing prediction models assisting in this task, which may be due to current conventional modeling ...
Machine Learning Consortium
core
Machine Learning in Image Steganalysis [PDF]
, 2012 Steganography is the art of communicating a secret message, hiding the very existence of a secret message. This is typically done by hiding the message within a non-sensitive document. Steganalysis is the art and science of detecting such hidden messages.
Vrusias, Bogdan, Schaathun, Hans Georg
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Digital Cognitive Phenotyping for Differential Diagnosis and Monitoring in Neurological Conditions
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To assess the utility, accessibility, and equivalence to supervised scales of online cognitive assessment in older individuals with cognitive impairment. Methods Patients with Alzheimer's disease (AD, n = 31), idiopathic normal pressure hydrocephalus (iNPH, n = 26), and traumatic brain injury (TBI, n = 23) completed online cognitive ...
Martina Del Giovane +10 more
wiley +1 more source
Respiratory ResearchBackground Chronic Obstructive Pulmonary Disease (COPD) poses significant public health and economic challenges and performant prognostic models may be useful to direct treatment.
Luke A. Smith +5 more
doaj +1 more source