Office: FEC 3120, The best way to reach me for this class is
generally via Piazza. I check it once a day, usually around noon.
Office Hours: By appointment.
Note: I will always be available in my office during office hours. At other times, if my door is open, feel
free to come
in. If the door is closed, I'm probably at work on a paper, grant or research problem. Please come by
another time or make an appointment via email.
Class Info
The class meets 4-6:45 TH in CENT 1030.
Course Description
This course will cover mathematical topics in Geometric Methods in Computer Science, with an eye towards modern
applications (e.g. machine learning, big data, distributed computing).
The methodology will be mathematical i.e. theorems and proofs.
U. Maryland Notes,
Pages 41-44 give a good connection between convex hulls,
and upper/lower envelopes, Lecture 8 gives good connection between envelopes and linear programming.
Lecture 16 gives good connections between convex hulls
and Voronoi diagrams, and Delaunay triangulations
Voronoi Diagrams, Delaunay Triangulations and More Dual Transformations
You can embed an arbitrary metric into Euclidean space with O(log n) distortion (via Bourgain's
theorem, see also here).
Then, you can use Johnson-Lidenstrauss to project onto R^d where d = O(log n).
