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Found 4 papers, 0 papers with code
MTrainS: Improving DLRM training efficiency using heterogeneous memories
In Deep Learning Recommendation Models (DLRM), sparse features capturing categorical inputs through embedding tables are the major contributors to model size and require high memory bandwidth.
Attention network forecasts time-to-failure in laboratory shear experiments
Our data were generated in a laboratory setting using a biaxial shearing device with granular fault gouge intended to mimic the conditions of tectonic faults.
Cascaded Region-based Densely Connected Network for Event Detection: A Seismic Application
Because of the fact that some positive events are not correctly annotated, we further formulate the detection problem as a learning-from-noise problem.
A Naive Bayes machine learning approach to risk prediction using censored, time-to-event data
Predicting an individual's risk of experiencing a future clinical outcome is a statistical task with important consequences for both practicing clinicians and public health experts.
