The Sample Complexity of Learning Lipschitz Operators with respect to Gaussian Measures
The episode discusses "The Sample Complexity of Learning Lipschitz Operators with respect to Gaussian Measures." Hosts analyze how learning these operators is limited by data structure, finding that standard methods cannot achieve algebraic convergence rates. However, they conclude that using adaptive sampling and exploiting fast spectral decay can achieve rates arbitrarily close to optimal.