Oct 26 at 12pm (Zoom) -- Chen Dan (CMU CSD) -- Sharp Statistical Guarantees for Adversarially Robust Gaussian Classification -- AI Seminar sponsored by Morgan Stanley

[Shaojie Bai]

Hi all,

Just a reminder that the CMU AI Seminar is tomorrow 12pm-1pm:
https://cmu.zoom.us/j/93155268338?pwd=VVZYTFFEMTNLZlJVY1NmU1c3cXUzZz09   .

Chen Dan (CMU CSD) will be talking about his recent work on statistical
understanding of adversarial robustness.

Thanks,
Shaojie

On Sat, Oct 23, 2021 at 3:08 PM Shaojie Bai <shaojieb at cs.cmu.edu> wrote:

> Dear all,
>
> We look forward to seeing you *next Tuesday (10/26)* from *1**2:00-1:00
> PM (U.S. Eastern time)* for the next talk of our *CMU AI seminar*,
> sponsored by Morgan Stanley
> <https://www.morganstanley.com/about-us/technology/>.
>
> To learn more about the seminar series or see the future schedule, please
> visit the seminar website <http://www.cs.cmu.edu/~aiseminar/>.
>
> On 10/26, *Chen Dan* (CMU CSD) will be giving a talk on "*Sharp
> Statistical Guarantees for Adversarially Robust Gaussian Classification*".
>
> *Title*: Sharp Statistical Guarantees for Adversarially Robust Gaussian
> Classification
>
> *Talk Abstract*: Adversarial robustness has become a fundamental
> requirement in modern machine learning applications. Yet, there has been
> surprisingly little statistical understanding so far. In this work, we
> provide the first result of the optimal minimax guarantees for the excess
> risk for adversarially robust classification, under a Gaussian mixture
> model studied by Schmidt et al. 2018. The results are stated in terms of
> the Adversarial Signal-to-Noise Ratio (AdvSNR), which generalizes a similar
> notion for standard linear classification to the adversarial setting. We
> establish an excess risk lower bound and design a computationally efficient
> estimator that achieves this optimal rate. Our results built upon a minimal
> set of assumptions while covering a wide spectrum of adversarial
> perturbations including L_p balls for any p>1. Joint work with Yuting Wei
> and Pradeep Ravikumar.
>
> *Speaker Bio*:  Chen Dan is a 6th year Ph.D. student at Computer Science
> Department, Carnegie Mellon University, advised by Pradeep Ravikumar. His
> research interest is in the broad area of robust statistical learning, with
> an emphasis on the theoretical understanding and practical algorithms for
> learning under various types of adversarial distribution shift. Prior to
> joining CMU, Chen received his bachelor degree from School of EECS, Peking
> University in 2016.
>
> *Zoom Link*:
> https://cmu.zoom.us/j/93155268338?pwd=VVZYTFFEMTNLZlJVY1NmU1c3cXUzZz09
>
> Thanks,
> Shaojie Bai (MLD)
>
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