Data represented geometrically in high-dimensional vector spaces can be found in many applications. Images and videos, are often represented by assigning a dimension for every pix...
Neural-inspired branch predictors achieve very low branch misprediction rates. However, previously proposed implementations have a variety of characteristics that make them challen...
Aggregating statistical representations of classes is an important task for current trends in scaling up learning and recognition, or for addressing them in distributed infrastruc...
Dimension reduction is popular for learning predictive models in high-dimensional spaces. It can highlight the relevant part of the feature space and avoid the curse of dimensiona...
Test suite reduction uses test requirement coverage to determine if the reduced test suite maintains the original suite’s requirement coverage. Based on observations from our pr...
Sreedevi Sampath, Sara Sprenkle, Emily Gibson, Lor...