Results 41 to 50 of about 8,505,406 (249)
Towards a Theory of Representation Learning for Reinforcement Learning
Presented online via Bluejeans Events on September 15, 2021 at 12:15 p.m.Alekh Agarwal is a researcher who works on theoretical foundations of machine learning, spanning many areas including large-scale and distributed optimization, high-dimensional ...
Agarwal, Alekh
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Digital Cognitive Phenotyping for Differential Diagnosis and Monitoring in Neurological Conditions
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
Estimating causal effects with machine learning: A guide for ecologists
In ecology, there is a growing need to move beyond correlations to uncovering causal effects from observational data. With the parallel increase in big data and machine learning algorithms, the opportunity now exists to benefit from causal machine ...
Suchinta Arif
doaj +1 more source
Learning curves for decision making in supervised machine learning: a survey
Learning curves are a concept from social sciences that has been adopted in the context of machine learning to assess the performance of a learning algorithm with respect to a certain resource, e.g., the number of training examples or the number of ...
van Rijn J.N., Mohr F.
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ABSTRACT Objectives Focal cortical dysplasia (FCD) is the most common etiology of drug‐resistant epilepsy in children. Focal to bilateral tonic–clonic seizures (FBTCS) mark a high risk of drug‐resistant epilepsy and involve thalamocortical circuitry in their generation and propagation.
Hua Xie +8 more
wiley +1 more source
Predictive Value of Composite Inflammatory Markers for Stroke Prognosis: A Prospective Cohort Study
ABSTRACT Background Novel composite inflammatory markers' role in stroke prognosis is understudied, and the best predictor is unclear, requiring further exploration. Objectives This study aimed to systematically evaluate the associations of 6 novel composite inflammatory markers on stroke prognosis.
Bing Wu +7 more
wiley +1 more source
Structured Prediction - Beyond Support Vector Machine and Cross Entropy
Presented online via Bluejeans Events on September 29, 2021 at 12:15 p.m.Francis Bach is a researcher at INRIA in the Computer Science department of Ecole Normale Supérieure, in Paris, France.
Bach, Francis
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Anticoagulation Treatment Response Among Phenotypic ESUS Clusters: Evidence From CASPR
ABSTRACT Objective To evaluate treatment effect heterogeneity across phenotypic clusters of patients with cryptogenic embolic stroke using causal inference methods. Methods From a retrospective, multicenter cohort of patients with cryptogenic embolic stroke, we estimated the treatment effect of anticoagulation versus antiplatelet therapy in patients ...
Elena Badillo Goicoechea +53 more
wiley +1 more source
Video-Language Critic : Transferable Reward Functions for Language-Conditioned Robotics [PDF]
Publisher Copyright: © 2025, Transactions on Machine Learning Research.Natural language is often the easiest and most convenient modality for humans to specify tasks for robots.
Woungang, Isaac +6 more
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Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos +2 more
wiley +1 more source

