September 6, 2019
Stephen W. Hawking Auditorium
located in the
George P. and Cynthia Woods Mitchell Institute for Fundamental Physics & Astronomy
See Map Below
Registration Is Closed
Workshop Organizers:
Bani K Mallick, Susan M. Arseven `75 Chair in Data Science & Computational Statistics & Distinguished Professor, TAMU Statistics
PR Kumar, College of Engineering Chair in Computer Engineering & Distinguished Professor, TAMU
R. Devore, The Walter E. Koss Professor & Distinguished Professor of Mathematics, TAMU
Nick Duffield, Director, Texas A&M Institute of Data Science & Professor of Electrical Engineering, TAMU
Workshop Institutional Co-Organizer:
Texas A&M Institute of Data Science (TAMIDS)
The Texas A&M Institute of Data Science pursues new approaches to Data Science research, education, operations and partnership. These approaches cross college boundaries to connect elements of Data Science from engineering, technology, science and the humanities, and inform wider social challenges.
Keynote Speakers:
Richard Baraniuk, Victor E. Cameron Professor, Founder & Director of OpenStax, Rice University
Ron Devore, The Walter E. Koss Professor & Distinguished Professor of Mathematics, TAMU
Bin Yu, Chancellor’s Professor in the Departments of Statistics and Electrical Engineering & Computer Science, UC Berkeley
Samuel Kou, Professor of Statistics, Harvard University
Invited Speakers:
Anastasios Kyrillidis, Noah Harding Assistant Professor, Rice University
Abhra Sarkar, Assistant Professor, University of Texas at Austin
Mingyuan Zhou, Assistant Professor, University of Texas at Austin
Schedule:
8:15 – 9:15 Registration/Breakfast
9:15 – 9:30 Welcome & Introduction by Dr. Valen Johsnon & Dr. Bani Mallick
9:30 – 10:30 Bin Yu: PCS framework, interpretable machine learning, and deep neural networks (Chair: PR Kumar)
10:30 – 10:45 Break
10:45 – 11:45 Ronald DeVore: Nonlinear Approximation by Deep ReLU Networks (Chair: Yalchin Efendiev)
11:45 – 12:00 Break
12:00 – 12:30 Anastasios Kyrillidis: Implicit regularization and solution uniqueness in over-parameterized matrix sensing (Chair: Dileep Kalathil)
12:30 – 1:30 LUNCH (Invitation Only)
1:30 – 2:00 Mingyuan Zhou: Augment-REINFORCE-swap-merge estimator for gradient backpropagation through discrete layers (Chair: Anirban Bhattacharya)
2:00 – 2:15 Break
2:15 – 3:15 Richard Baraniuk: Mad Max: Affine Spline Insights into Deep Learning (Chair: Yu Ding)
3:15 – 3:30 Break
3:30 – 4:00 Abhra Sarkar: Bayesian Semi parametric Longitudinal Drift-Diffusion Mixed Models for Neural Decision-making (Chair: Debdeep Pati)
4:00 – 4:15 Break
4:15 – 5:15: Samuel Kou: Big data, Google and disease detection: a statistical adventure (Chair Jianhua Huang)
Reception to follow: 5:30-7:30 – Penrose Plaza – All Attendees Welcome
