[AI Seminar] AI Seminar sponsored by Apple -- Yaodong Yu -- Nov. 27th

[Han Zhao]

Dear faculty and students:

We look forward to seeing you next Tuesday, Nov. 27th, at noon in GHC 6115
for AI Seminar sponsored by Apple. To learn more about the seminar series,
please visit the website.
On Tuesday, Yaodong Yu will give the following talk:

*Title: Adversarial Defenses and Attacks: A Case Study on NIPS 2018
Adversarial Vision Challenge*

*Abstract: *In recent years, we have witnessed the success of machine
learning, especially deep learning, in various areas. Despite widespread
adoption, recent studies have shown that machine learning models are
vulnerable to adversarial examples, i.e., very small changes to inputs can
cause machine learning models to make mistakes. Thus, understanding and
defending against adversarial examples is crucial to the AI security and
interpretability concerns.

In this talk, we will focus on how to train robust models and generate
adversarial examples in the NIPS 2018 Adversarial Vision Challenge. In the
first part of the talk, we will briefly introduce basic adversarial defense
and attack techniques as well as the rule in the NIPS 2018 Adversarial
Vision Challenge. In the second part of the talk, we will present several
take-home messages on how to train robust models efficiently on large-scale
datasets (Tiny ImageNet) by using deep convolutional neural networks (e.g.,
ResNet152). In addition, we will present our approach on generating
adversarial examples for targeted attacks.

Based on joint work with Hongyang Zhang (CMU), Susu Xu (CMU), Hongbao Zhang
(Petuum), Pengtao Xie (Petuum) and Eric P. Xing (CMU and Petuum).
-- 

*Han ZhaoMachine Learning Department*


*School of Computer ScienceCarnegie Mellon UniversityMobile: +1-*
*412-652-4404*
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