Research Symposium Posters

Five students from our group presented posters at the department’s Fall Research Symposium:


Anshuman Suri’s Overview Talk


Bargav Jayaraman, Evaluating Differentially Private Machine Learning In Practice [Poster]
[Paper (USENIX Security 2019)]




Hannah Chen [Poster]




Xiao Zhang [Poster]
[
Paper (NeurIPS 2019)]




Mainudding Jonas [Poster]




Fnu Suya [Poster]
[
Paper (USENIX Security 2020)]

Cost-Sensitive Adversarial Robustness at ICLR 2019

Xiao Zhang will present Cost-Sensitive Robustness against Adversarial Examples on May 7 (4:30-6:30pm) at ICLR 2019 in New Orleans.

Paper: [PDF] [OpenReview] [ArXiv]

Empirically Measuring Concentration

Xiao Zhang and Saeed Mahloujifar will present our work on Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness at two workshops May 6 at ICLR 2019 in New Orleans: Debugging Machine Learning Models and Safe Machine Learning: Specification, Robustness and Assurance.

Paper: [PDF]

ICLR 2019: Cost-Sensitive Robustness against Adversarial Examples

Xiao Zhang and my paper on Cost-Sensitive Robustness against Adversarial Examples has been accepted to ICLR 2019. Several recent works have developed methods for training classifiers that are certifiably robust against norm-bounded adversarial perturbations. However, these methods assume that all the adversarial transformations provide equal value for adversaries, which is seldom the case in real-world applications. We advocate for cost-sensitive robustness as the criteria for measuring the classifier’s performance for specific tasks.

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