[CMU AI Seminar] Nov 23 at 12pm (Zoom) -- Eric Wallace (UC Berkeley) -- What Can We Learn From Vulnerabilities of ML Models? -- AI Seminar sponsored by Morgan Stanley

[Shaojie Bai]

Dear all,

Eric Wallace's (UC Berkeley) talk on large-scale NLP models and robustness
is starting now! Zoom:
https://cmu.zoom.us/j/96673560117?pwd=WHFMWERjWkphbnlNMWl2cmk5aE1QZz09

Best,
Shaojie

On Mon, Nov 22, 2021 at 4:10 PM Shaojie Bai <shaojieb at cs.cmu.edu> wrote:

> Hi all,
>
> Just a reminder that the CMU AI Seminar
> <http://www.cs.cmu.edu/~aiseminar/> is tomorrow *12pm-1pm*:
> https://cmu.zoom.us/j/96673560117?pwd=WHFMWERjWkphbnlNMWl2cmk5aE1QZz09.
>
> *Eric Wallace* (UC Berkeley) will be talking about large-scale NLP models
> and the their vulnerabilities (see below)!
>
> --------------------------------------
> *Title:*  What Can We Learn From Vulnerabilities of ML Models?
>
> *Talk Abstract:* Today's neural network models achieve high accuracy on
> in-distribution data and are being widely deployed in production systems.
> This talk will discuss attacks on such models that not only expose
> worrisome security and privacy vulnerabilities, but also provide new
> perspectives into how and why the models work. Concretely, I will show how
> realistic adversaries can extract secret training data, steal model
> weights, and manipulate test predictions, all using black-box access to
> models at either training- or test-time. These attacks will reveal
> different insights, including how NLP models rely on dataset biases and
> spurious correlations, and how their training dynamics impact memorization
> of examples. Finally, I will discuss defenses against these vulnerabilities
> and suggest practical takeaways for developing secure ML systems.
>
> *Speaker Bio: *Eric Wallace is a 3rd year PhD student at UC Berkeley
> advised by Dan Klein and Dawn Song. His research interests center around
> large language models and making them more secure, private, and robust.
> Eric's work received the best demo award at EMNLP 2019.
> --------------------------------------
>
> Thanks and Happy Thanksgiving,
> Shaojie
>
>
> On Fri, Nov 19, 2021 at 12:51 PM Shaojie Bai <shaojieb at cs.cmu.edu> wrote:
>
>> Dear all,
>>
>> We look forward to seeing you *next Tuesday (11/23)* 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 11/23, *Eric Wallace* (UC Berkeley) will be giving a talk on "*What
>> can we learn from vulnerabilities of ML models*" and sharing his latest
>> research on large-scale NLP models and their vulnerabilities.
>>
>> *Title:*  What Can We Learn From Vulnerabilities of ML Models?
>>
>> *Talk Abstract:* Today's neural network models achieve high accuracy on
>> in-distribution data and are being widely deployed in production systems.
>> This talk will discuss attacks on such models that not only expose
>> worrisome security and privacy vulnerabilities, but also provide new
>> perspectives into how and why the models work. Concretely, I will show how
>> realistic adversaries can extract secret training data, steal model
>> weights, and manipulate test predictions, all using black-box access to
>> models at either training- or test-time. These attacks will reveal
>> different insights, including how NLP models rely on dataset biases and
>> spurious correlations, and how their training dynamics impact memorization
>> of examples. Finally, I will discuss defenses against these vulnerabilities
>> and suggest practical takeaways for developing secure ML systems.
>>
>> *Speaker Bio: *Eric Wallace is a 3rd year PhD student at UC Berkeley
>> advised by Dan Klein and Dawn Song. His research interests center around
>> large language models and making them more secure, private, and robust.
>> Eric's work received the best demo award at EMNLP 2019.
>>
>> *Zoom Link: *
>> https://cmu.zoom.us/j/96673560117?pwd=WHFMWERjWkphbnlNMWl2cmk5aE1QZz09
>>
>> Best,
>> Shaojie Bai (MLD)
>>
>
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