ML for Systems

ML for Systems examines learning methods across the computing stack. Topics include automated design and optimization of data structures, circuits, compilers, databases, operating systems and cloud resources, connecting generative agents with the practical challenges of building and evaluating computer systems. Session: 08:00–17:00 (Australia/Sydney). A paid NeurIPS virtual pass includes workshop livestreams; on-site access follows the host-location registration rules.