3 citations · 3 across the 6 of their papers we have counts for
6 papers
Fast algorithms for learning a Gaussian under halfspace truncation with optimal sample complexity
Haitong Liu, Deepak Narayanan Sridharan, David Steurer +1
We study the fundamental problem of learning a high-dimensional Gaussian truncated to an unknown halfspace. Lee, Mehrotra and Zampetakis (FOCS'24) recently obtained the first polyn…
Agnostic learning in (almost) optimal time via Gaussian surface area
Lucas Pesenti, Lucas Slot, Manuel Wiedmer
The complexity of learning a concept class under Gaussian marginals in the difficult agnostic model is closely related to its -approximability by low-degree polynomials. For a…
Hesse's Redemption: Efficient Convex Polynomial Programming
Lucas Slot, David Steurer, Manuel Wiedmer
Efficient algorithms for convex optimization, such as the ellipsoid method, require an a priori bound on the radius of a ball around the origin guaranteed to contain an optimal sol…
Testably Learning Polynomial Threshold Functions
Lucas Slot, Stefan Tiegel, Manuel Wiedmer
Rubinfeld & Vasilyan recently introduced the framework of testable learning as an extension of the classical agnostic model. It relaxes distributional assumptions which are difficu…
Nonconvergence of a sum-of-squares hierarchy for global polynomial optimization based on push-forward measures
Lucas Slot, Manuel Wiedmer
Let be a closed set, and consider the problem of computing the minimum of a polynomial on . Given a measure suppo…
Right-angled Artin groups as finite-index subgroups of their outer automorphism groups
Manuel Wiedmer
We prove that every right-angled Artin group occurs as a finite-index subgroup of the outer automorphism group of another right-angled Artin group. We furthermore show that the lat…