Machine Learning

The 2022 Women and Mathematics (WAM) program took place from May 21–27, bringing together 40 students, educators, and researchers from universities around the world to participate in a series of lectures, problem sessions, research seminars, and special talks around the theme “The Mathematics of Machine Learning.” The program returned to campus for the first time since 2019 after being postponed in 2020 and held remotely in 2021.

"If an adversary gives you a machine learning model and secretly plants a malicious backdoor in it, what are the chances that you can discover it? Very little, according to a new paper by researchers at UC Berkeley, MIT, and the Institute for Advanced Study."

"For more than 250 years, mathematicians have been trying to 'blow up' some of the most important equations in physics: those that describe how fluids flow. If they succeed, then they will have discovered a scenario in which those equations break down — a vortex that spins infinitely fast, perhaps, or a current that abruptly stops and starts, or a particle that whips past its neighbors infinitely quickly."

Ronen Eldan, current von Neumann Fellow in the School of Mathematics, has received a 2022 Blavatnik Award for his profound contributions to statistics, machine learning, and theoretical computer science.

"...maybe this paradigm of the usefulness of useless knowledge is what the Danish physicist Niels Bohr liked to call a “great truth” — a truth whose opposite is also a great truth. Maybe, as AI is demonstrating, knowledge can also flow uphill."