Matrix completion is a well-studied problem with many machine learning applications. In practice, the problem is often solved by non-convex optimization algorithms. However, the current theoretical analysis for non-convex algorithms relies heavily on the assumption…
Episode 19, April 11, 2018 – Dr. Lauter tells us why she feels lucky to do math for a living, explains the singular beauty of elliptic curves and the singular difficulty of supersingular isogeny graphs,…
What an exciting two days at the Second Homomorphic Encryption Standardization Workshop at Massachusetts Institute of Technology. More than 70 participants from 10 countries gathered together for two intense days of panels, discussions and planning…
We introduce a general model of bandit problems in which the expected payout of an arm is an increasing concave function of the time since it was last played. We first develop approximation algorithms for…
John’s theorem proved in 1948 states that any centrally-symmetric convex body in R^d can be sandwiched by two ellipsoids up to a factor of sqrt{d}. In particular, it implies that any d-dimensional normed space embeds…
Recent discussion in the public sphere about classification by algorithms has involved tension between competing notions of what it means for such a classification to be fair to different groups. We consider several of the…
