[Theory] TODAY: 10/27 TTIC Colloquium: Tselil Schramm, Stanford University

[Mary Marre]

*When:*        Friday, October 27, 2023 at* 10:30** a**m CT   *


*Where:       *Talk will be given *live, in-person* at

                   TTIC, 6045 S. Kenwood Avenue

                   5th Floor, Room 530


*Virtually:*  *via *Panopto (*livestream
<https://uchicago.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=ae4322fa-9067-4b60-821e-b0a2001ab975>*
)

*                        *limited access: see info below*


*Who: *         Tselil Schramm, Stanford University

------------------------------
*Title:         *Spectral Clustering in High-Dimensional Gaussian Mixture
Block Models

*Abstract: *The Gaussian mixture block model is a simple generative model
for networks: to generate a sample, we associate each node with a latent
feature vector sampled from a mixture of Gaussians, and we add an edge
between nodes if and only if their feature vectors are sufficiently
similar. The different components of the Gaussian mixture represent the
fact that there may be several types of nodes with different distributions
over features -- for example, in a social network each component represents
the different attributes of a distinct community.  In this talk I will
discuss recent results on the performance of spectral clustering algorithms
on networks sampled from high-dimensional Gaussian mixture block models,
where the dimension of the latent feature vectors grows as the size of the
network goes to infinity. Our results merely begin to sketch out the
information-computation landscape for clustering in these models, and I
will make an effort to emphasize open questions.

Based on joint work with Shuangping Li.
Host: *Madhur Tulsiani* <madhurt at ttic.edu>

*Access to this livestream is limited to TTIC / UChicago (press panopto
link and sign in to your UChicago account with CNetID).



Mary C. Marre
Faculty Administrative Support
*Toyota Technological Institute*
*6045 S. Kenwood Avenue, Rm 517*
*Chicago, IL  60637*
*773-834-1757*
*mmarre at ttic.edu <mmarre at ttic.edu>*


On Thu, Oct 26, 2023 at 4:47 PM Mary Marre <mmarre at ttic.edu> wrote:

> *When:*        Friday, October 27, 2023 at* 10:30** a**m CT   *
>
>
> *Where:       *Talk will be given *live, in-person* at
>
>                    TTIC, 6045 S. Kenwood Avenue
>
>                    5th Floor, Room 530
>
>
> *Virtually:*  *via *Panopto (*livestream
> <https://uchicago.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=ae4322fa-9067-4b60-821e-b0a2001ab975>*
> )
>
> **limited access: see info below*
>
>
> *Who: *         Tselil Schramm, Stanford University
>
> ------------------------------
> *Title:         *Spectral Clustering in High-Dimensional Gaussian Mixture
> Block Models
>
> *Abstract: *The Gaussian mixture block model is a simple generative model
> for networks: to generate a sample, we associate each node with a latent
> feature vector sampled from a mixture of Gaussians, and we add an edge
> between nodes if and only if their feature vectors are sufficiently
> similar. The different components of the Gaussian mixture represent the
> fact that there may be several types of nodes with different distributions
> over features -- for example, in a social network each component represents
> the different attributes of a distinct community.  In this talk I will
> discuss recent results on the performance of spectral clustering algorithms
> on networks sampled from high-dimensional Gaussian mixture block models,
> where the dimension of the latent feature vectors grows as the size of the
> network goes to infinity. Our results merely begin to sketch out the
> information-computation landscape for clustering in these models, and I
> will make an effort to emphasize open questions.
>
> Based on joint work with Shuangping Li.
> Host: *Madhur Tulsiani* <madhurt at ttic.edu>
>
> *Access to this livestream is limited to TTIC / UChicago (press panopto
> link and sign in to your UChicago account with CNetID).
>
>
>
>
> Mary C. Marre
> Faculty Administrative Support
> *Toyota Technological Institute*
> *6045 S. Kenwood Avenue, Rm 517*
> *Chicago, IL  60637*
> *773-834-1757*
> *mmarre at ttic.edu <mmarre at ttic.edu>*
>
>
> On Fri, Oct 20, 2023 at 8:49 PM Mary Marre <mmarre at ttic.edu> wrote:
>
>> *When:*        Friday, October 27, 2023 at* 10:30** a**m CT   *
>>
>>
>> *Where:       *Talk will be given *live, in-person* at
>>
>>                    TTIC, 6045 S. Kenwood Avenue
>>
>>                    5th Floor, Room 530
>>
>>
>> *Virtually:*  *via *Panopto (*livestream
>> <https://uchicago.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=ae4322fa-9067-4b60-821e-b0a2001ab975>*
>> )
>>
>> * *limited access: see info below*
>>
>>
>> *Who: *         Tselil Schramm, Stanford University
>>
>> ------------------------------
>> *Title:         *Spectral Clustering in High-Dimensional Gaussian
>> Mixture Block Models
>>
>> *Abstract: *The Gaussian mixture block model is a simple generative
>> model for networks: to generate a sample, we associate each node with a
>> latent feature vector sampled from a mixture of Gaussians, and we add an
>> edge between nodes if and only if their feature vectors are sufficiently
>> similar. The different components of the Gaussian mixture represent the
>> fact that there may be several types of nodes with different distributions
>> over features -- for example, in a social network each component represents
>> the different attributes of a distinct community.  In this talk I will
>> discuss recent results on the performance of spectral clustering algorithms
>> on networks sampled from high-dimensional Gaussian mixture block models,
>> where the dimension of the latent feature vectors grows as the size of the
>> network goes to infinity. Our results merely begin to sketch out the
>> information-computation landscape for clustering in these models, and I
>> will make an effort to emphasize open questions.
>>
>> Based on joint work with Shuangping Li.
>> Host: *Madhur Tulsiani* <madhurt at ttic.edu>
>>
>> *Access to this livestream is limited to TTIC / UChicago (press panopto
>> link and sign in to your UChicago account with CNetID).
>>
>>
>>
>> Mary C. Marre
>> Faculty Administrative Support
>> *Toyota Technological Institute*
>> *6045 S. Kenwood Avenue, Rm 517*
>> *Chicago, IL  60637*
>> *773-834-1757*
>> *mmarre at ttic.edu <mmarre at ttic.edu>*
>>
>
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