Seminar

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Monday, February 8, 2021 12:00 pm - 12:00 pm EST (GMT -05:00)

Seminar • Machine Learning — New Advances in (Adversarially) Robust and Secure Machine Learning

Please note: This seminar will be given online.

Hongyang Zhang, Postdoctoral Fellow
Toyota Technological Institute at Chicago

Deep learning models are often vulnerable to adversarial examples. In this talk, we will focus on robustness and security of machine learning against adversarial examples. There are two types of defenses against such attacks: 1) empirical and 2) certified adversarial robustness.

Tuesday, February 2, 2021 12:00 pm - 12:00 pm EST (GMT -05:00)

Seminar • Natural Language Processing | Machine Learning — Reliable Machine Learning for Computational Social Science

Please note: This seminar will be given online.

Dallas Card, Postdoctoral scholar
NLP Group and the Data Science Institute, Stanford University

Machine learning and natural language processing have become increasingly influential, both in commercial applications and as key tools for research in the natural and social sciences. In both cases, however, research in these fields raises numerous concerns related to bias, transparency, robustness, and how we communicate information.

Tuesday, January 26, 2021 12:00 pm - 12:00 pm EST (GMT -05:00)

Seminar • Algorithms and Complexity — Diversity and Fairness in Data Summarization Algorithms

Please note: This seminar will be given online.

Sepideh Mahabadi
Toyota Technological Institute at Chicago

Searching and summarization are two of the most fundamental tasks in massive data analysis. In this talk, I will focus on these two tasks from the perspective of diversity and fairness.