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Tuesday, March 22, 2022 11:30 am - 11:30 am EDT (GMT -04:00)

Seminar • Artificial Intelligence • Toward Reliable Machine Learning with Instruments

Please note: This seminar will be given online.

Krikamol Muandet
Research Group Leader, Empirical Inference Department
Max Planck Institute for Intelligent Systems

Society is made up of a set of diverse individuals, demographic groups, and institutions. Learning and deploying algorithmic models across these heterogeneous environments face a set of various trade-offs. In order to develop reliable machine learning algorithms that can interact successfully with the real world, it is necessary to deal with such heterogeneity.

Please note: This seminar will be given online.

Sushant Sachdeva, Assistant Professor
Department of Computer Science, University of Toronto

We give the first almost-linear time algorithm for computing exact maximum flows and minimum-cost flows on directed graphs. By well known reductions, this implies almost-linear time algorithms for several problems including bipartite matching, optimal transport, and undirected vertex connectivity.

Please note: This PhD seminar will be given online.

Ludwig Wilhelm Wall, PhD candidate
David R. Cheriton School of Computer Science

Supervisors: Professors Daniel Vogel, Oliver Schneider