Ziwei Zhu, PhD candidate
Department of Computer Science and Engineering, Texas A&M University
Stavros Sintos, Postdoctoral Scholar
Department of Computer Science, University of Chicago
Xiao Hu, Visiting Researcher
Discrete Algorithm Group, Google Research
Zihao Wang, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Lila Kari
Jiayi Chen, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Urs Hengartner
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.
Ludwig Wilhelm Wall, PhD candidate
David R. Cheriton School of Computer Science
Supervisors: Professors Daniel Vogel, Oliver Schneider
Malavika Samak, Postdoctoral Associate
Computer Science and Artificial Intelligence Laboratory, MIT
Ruosong Wang
School of Computer Science, Carnegie Mellon University
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.