Momentum-based async SGD achieves optimal convergence rates for data-dependent delays without biasing updates toward simpler samples.
Grid search, random search, genetic algorithm: a big comparison for nas
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A three-phase ML-assisted curation creates a Cardiology Interface Terminology (CIT) from SNOMED and EHR data that highlights details in cardiology notes with 74.21% coverage, 98.2% average completeness, and 84.2% average conciseness on test data.
A survey of Spiking Neural Network architecture search techniques viewed through a hardware/software co-design lens.
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Bringing Order to Asynchronous SGD: Towards Optimality under Data-Dependent Delays with Momentum
Momentum-based async SGD achieves optimal convergence rates for data-dependent delays without biasing updates toward simpler samples.
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Curation of a Cardiology Interface Terminology for Highlighting Electronic Health Records using Machine Learning
A three-phase ML-assisted curation creates a Cardiology Interface Terminology (CIT) from SNOMED and EHR data that highlights details in cardiology notes with 74.21% coverage, 98.2% average completeness, and 84.2% average conciseness on test data.
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Spiking Neural Network Architecture Search: A Survey
A survey of Spiking Neural Network architecture search techniques viewed through a hardware/software co-design lens.