Mathematics of Data and Decision at Davis Seminar
This new seminar series by the UC Davis Math Department kicks off on October 1st at 3pm, and is held weekly 45 thereafter for Fall 2018 in MASB 1147.
Fall MADDD Schedule
Mondays 45pm in MSB1147 (unless otherwise specified)

Oct 1: Jorge Nocedal (Northwestern), Andrea Montanari (Stanford), Joel Tropp (Caltech)  start time of 2pm
2:00PM Jorge Nocedal, Northwestern University. Nonlinear Optimization Methods for Machine Learning 3:00PM Andrea Montanari Stanford University. A Mean Field View of the Landscape of TwoLayers Neural Networks 4:30PM Joel Tropp, Caltech. Applied random matrix theory
 Oct 8: Ery AriasCastro (UCSD)
 Oct 15: Aaron Sidford (Stanford)
 Oct 22: Lihong Li (Google)
 Oct 29: Sayan Mukherjee (Duke)
 Nov 5: Madeleine Udell (Cornell)
 Nov 12: No seminar. University Holiday.
 Nov 19: Boaz Nadler (Weizmann Institute of Science)
 Nov 26: Jelena Diakonikolas (UC Berkeley)
 Dec 3: Anna Ma (UCSD)
 Dec 10: Paul Grigas (UC Berkeley)
About MADDD
The MADDD seminar aims to gather researchers on all kinds of cuttingedge algorithmic and mathematical techniques used when analyzing and visualizing data, and then making optimal decisions. Thus talks and discussions on the seminar, most often directly motivated by applications, will include (but will not be limited to): Optimization, Applied Computational Harmonic Analysis, Topological Data Analysis, Game Theory, Information theory, Theory of Machine Learning Algorithms, Computational Geometry, Inverse problems, Shape optimization problems, Scheduling problems, Packing, Risk assessment models, Control theory, Computer vision problems, Statistical signal and image processing, Pattern Recognition problems, Clustering and classification, Data Compression, Discrete Mathematics, Numerical Linear and Tensor Algebra, Random matrix theory, Convex and Functional analysis, etc. For more information see the MADDD seminar webpage. Questions? Contact Shiqian Ma.