Browsing: Ryan

The original version of ““It was really exciting,” said “, a doctoral student at the University of California, San Diego. Researchers worked to optimize LLL-style algorithms to accommodate bigger inputs, often achieving good performance. Still, some tasks have remained stubbornly out of reach. The new paper, authored by Ryan and his adviser, Nadia Heninger, combines