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Please note: This seminar will be given online.

Shalmali Joshi, Postdoctoral Fellow
Center for Research on Computation and Society, Harvard University

Machine Learning advances have revolutionized many domains such as machine translation, complex game playing, and scientific discovery. On the other hand, ML has only enjoyed modest successes in human-centered applications. To improve the utility, reliability, and robustness of Machine Learning (ML) models in human-centered domains, we need to address several foundational challenges.

Please note: This seminar will be given online.

Yue Dong
School of Computer Science, McGill University
Mila

Natural language processing (NLP) offers incredible opportunities for automating tasks that involve human languages. However, numerous studies show that instead of learning, modern systems frequently memorize artifacts and biases. Furthermore, the texts produced by such models often contain factual errors.

Milind Tambe
Gordon McKay Professor of Computer Science
Director of the Center for Research in Computation and Society, Harvard University
Director, AI for Social Good, Google Research India