AMS Fall Central Sectional Meeting
Dates: September 14-15, 2019 (Saturday – Sunday)
Venue: Room 104, Van Hise Hall, University of Wisconsin-Madison
Organizers:
Sebastien Roch (UW-Madison), David Sivakoff (OSU), Joseph Watkins (UA)
In a collaboration between the NSF TRIPODS Institutes at the University of Wisconsin-Madison (IFDS), the Ohio State University (TGDA@OSU), and the University of Arizona (UA-TRIPODS), this special session will cover a number of mathematical areas of relevance to data science, including topological data analysis, stochastic processes on graphs, optimization theory and more. A particular emphasis will be on recent work at the critical trans-disciplinary interface of mathematics, computer science and statistics.
Speakers
Mireille Boutin, Purdue University
Guy Bresler, Massachusetts Institute of Technology
Constantinos Daskalakis, Massachusetts Institute of Technology
Michal Derezinski, UC Berkeley
Vu C Dinh, University of Delaware
Keaton Hamm, University of Arizona
Mina Karzand, University of Wisconsin-Madison
Sebastian Kurtek, The Ohio State University
William Lippitt, University of Arizona
Blake Mason, University of Wisconsin-Madison
Marina Meila, University of Washington
Michael O’Neill, University of Wisconsin-Madison
Miklos Racz, Princeton University
Benjamin Schweinhart, The Ohio State University
Ashia Wilson, Microsoft Research (to be confirmed)
Helen Zhang, University of Arizona
Yuqian Zhang, Cornell University
Schedule
Saturday September 14, 2019
8:30 a.m.-11:20 a.m.
Room 104, Van Hise Hall
| 08:30 | Markovian Stick-breaking Measures and Clumping Procedures William Lippitt, University of Arizona |
| 09:00 | A Log-barrier Newton-CG Method for Bound Constrained Optimization with Complexity Guarantees Michael O’Neill, University of Wisconsin, Madison |
| 9:30 | Trace reconstruction problems with applications to DNA data storage Miklos Z Racz, Princeton University |
| 10:00 | Learning a Tree-Structured Ising Model in Order to Make Predictions Mina Karzand, University of Wisconsin, Madison |
| 10:30 | Nonconvex Geometry for Blind Deconvolution Yuqian Zhang, Cornell University |
| 11:00 | Geometric methods for image-based statistical analysis of brain tumors Sebastian Kurtek, The Ohio State University |
Saturday September 14, 2019
2:00 p.m.-4:50 p.m.
Room 104, Van Hise Hall
| 2:00 | Average-Case Reductions Between Statistics Problems: From GOE to Wishart and Other Precise Distributional Maps Guy Bresler, Massachusetts Institute of Technology |
| 2:30 | Scalable and Model-free Methods for Multiclass Probability Estimation Helen Zhang, University of Arizona |
| 3:00 | Unbiased estimators for random design regression Michal Derezinski, UC Berkeley |
| 3:30 | Fractal Dimension Estimation with Persistent Homology Benjamin Schweinhart, The Ohio State University |
| 4:00 | Statistical learning with evolutionary-related correlated random variables Vu C Dinh, University of Delaware |
| 4:30 | Reducing AI Bias using Truncated Statistics Constantinos Daskalakis, EECS and CSAIL, MIT |
Sunday September 15, 2019
8:30 a.m.-10:50 a.m.
Room 104, Van Hise Hall
| 08:30 | Clustering small datasets in high-dimension using random projection Mireille Boutin, Purdue University |
| 9:00 | Learning nearest neighbor graphs from noisy distance samples Blake J Mason, University of Wisconsin – Madison |
| 9:30 | Multi-Level Graph Spanners Keaton Hamm, University of Arizona |
| 10:00 | Is Manifold Learning for toy data only? Marina Meila, University of Washington |
| 10:30 | Discussion |
Abstracts can be found here: http://www.ams.org/meetings/sectional/2267_program_ss39.html