— We introduce a transformation, named rephasing, that manipulates the timing parameters in control-data-flow graphs (CDFG’s) during the high-level synthesis of data-pathinten...
Abstract In case of insufficient data samples in highdimensional classification problems, sparse scatters of samples tend to have many ‘holes’—regions that have few or no nea...
Hakan Cevikalp, Diane Larlus, Marian Neamtu, Bill ...
The Compressive Sensing (CS) framework aims to ease the burden on analog-to-digital converters (ADCs) by reducing the sampling rate required to acquire and stably recover sparse s...
Laurent Jacques, Jason N. Laska, Petros Boufounos,...
Scarcity and infeasibility of human supervision for large
scale multi-class classification problems necessitates active
learning. Unfortunately, existing active learning methods
...
Prateek Jain (University of Texas at Austin), Ashi...
This paper addresses the problem of computing visual hulls from image contours. We propose a new hybrid approach which overcomes the precision-complexity trade-off inherent to vox...