Dan Spielman (Yale University) discusses expander graphs, laplacians matrices, and his CMSA public talk as part of the Special Program on Combinatorics and Complexity.
Title: The Laplacian Matrices of Graphs: Algorithms and Applications
Abstract: The Laplacian matrices of graphs arise in many fields, including Machine Learning, Computer Vision, Optimization, Computational Science, and of course Network Analysis. We will explain what these matrices are and why they appear in so many applications.
We then survey recent ideas that allow us to solve systems of linear equations in Laplacian matrices in nearly linear time, emphasizing the utility of graph sparsification—the approximation of a graph by a sparser one—and a recent algorithm of Kyng and Sachdeva that uses random sampling to accelerate Gaussian Elimination.
Stephen Hawking passed away yesterday. He was 76. He visited the Black Hole Initiative in 2016 (pictured above). In 2006, Prof. Shing-Tung Yau helped arrange Prof. Hawking’s visit to China, where he has remained a popular cultural figure. In the words of Prof. Yau, “He was very friendly and was willing to explain physics to laymen…. Continue reading
Hansol Hong (CMSA Postdoc) describes his current research at the Center of Mathematical Sciences and Applications.
Check out the program page for the Simons Collaboration on Homological Symmetry here: https://cmsa.fas.harvard.edu/simons-collaboration-on-homological-mirror-symmetry/
Benny Sudakov (ETH Zürich) describes the topics and goals of the Workshop on Extremal and Probabilistic Combinatorics and the importance of collaboration in science and math.
The Simons Collaboration Workshop on Homological Mirror Symmetry and Hodge Theory was held January 10-13. Learn more about the Simons Collaboration here.
During the Spring 2018 Semester Artan Sheshmani (QGM/CMSA) will be teaching a CMSA special lecture series on Quantum Cohomology, Nakajima Vareties and Quantum groups. The lectures will be held Tuesdays and Thursdays, from 1:00 to 3:00pm in room G10, CMSA Building.