US Patent Issued to XILINX on May 26 for "Exploiting learned saliency to optimize machine learning training" (British, American Inventors)

ALEXANDRIA, Va., May 26 -- United States Patent no. 12,639,616, issued on May 26, was assigned to XILINX INC. (San Jose, Calif.).

"Exploiting learned saliency to optimize machine learning training" was invented by Erwei Wang (London) and Samuel R. Bayliss (Mountain View, Calif.).

According to the abstract* released by the U.S. Patent & Trademark Office: "Embodiments herein describe techniques for setting and using saliency values to modify how a ML model is trained. In one embodiment, different blocks of data (referred to herein as tiles) are assigned respective saliency values. After performing one or more iterations, a training application can modify the default saliency values assigned to the tiles to reflect the importance of the tile...