#  Probabilitas Seminar: Alex Damian 

 



####  calendar\_today Date and Time 

 **October 28, 2025** 

 01:30PM - 02:30PM EDT 

####  pin\_drop Location 

 **Science Center 705**  



 

 



 

The Probabilitas Seminar series focuses on high-dimensional problems that combine statistics, probability, artificial intelligence, information theory, computer science, and other related fields. The upcoming seminar takes place on Tuesday, October 28, at 1:30pm in **Science Center 705**. This week's speaker will be **Alex Damian**, research fellow at the Harvard Kempner Institute.

**Learning From Gaussian Data: Single and Multi-Index Models**

Abstract: In this work we consider generic Gaussian Multi-index models, in which the labels only depend on the (Gaussian) d-dimensional inputs through their projection onto a low-dimensional subspace, and we study efficient agnostic estimation procedures for this hidden subspace. We introduce the generative leap exponent k\*, a natural extension of the generative exponent from \[DPVLB24\] to the multi-index setting. We first show that a sample complexity of n= Θ(d^{1∨k\*/2}) is necessary in the class of algorithms captured by the Low-Degree-Polynomial framework. We then establish that this sample complexity is also sufficient, by giving an agnostic sequential estimation procedure (that is, requiring no prior knowledge of the multi-index model) based on a spectral U-statistic over appropriate Hermite tensors. We further compute the generative leap exponent for several examples including piecewise linear functions (deep ReLU networks with bias).

Topic: Alex Damian seminar

Time: Oct 28, 2025 01:30 PM Eastern Time (US and Canada)

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