Location
This summer school was held at the Hamner Conference Center in Research Triangle Park, NC.
Description
The Summer School will introduce graduate students and early-career researchers in the Mathematical and Statistical Sciences to the mathematical and statistical approaches in Optimization, and their applications.
Each day will be devoted to a specific topic. Topics under consideration include: E/M & M/M algorithms; statistical and mathematical inverse problems; optimization under uncertainty; convex and semidefinite optimization; robust optimization, sparse regression, and stochastic gradient descent; mixed integer, linear & nonlinear optimization; and PDE-constrained optimization. Applications to be considered include: machine learning; image & signal processing; and compressed sensing.
Questions: email [email protected]
Schedule and Supporting Media
Speakers Bios Titles/Abstracts
Participants
Posters
Monday, August 8, 2016
Hamner Conference Center RTP
| Description | Speaker | Slides | Videos |
|---|---|---|---|
| Opening Remarks | Ilse Ipsen, SAMSI | ||
| “Computational Methods for PDE Constrained Optimization” | Volker Schulz, University of Trier | ||
| PDE Constrained Optimization vs. Nonlinear Programming | Volker Schulz, University of Trier | ||
| Theory on PDE Constrained Shape Optimization | Volker Schulz, University of Trier | ||
| PDE Constrained Optimization in HPC and Applications | Volker Schulz, University of Trier |
Tuesday, August 9, 2016
Hamner Conference Center RTP
| Description | Speaker | Slides | Videos |
|---|---|---|---|
| “Hippylib: An Extensive Software Framework for large-Scale Detrministic and Linearized Bayesian Inverse Problems” | Noemi Petra, University of California, Merced | ||
| Inverse problems and Uncertainty Quantification: Motivation and Challenges | Noemi Petra, University of California, Merced | ||
| Deterministic Inversion: Solution Methods (1st & 2nd Order adjoints, gradients, Hessian-applies, inexact Newton-CG) | Noemi Petra, University of California, Merced | ||
| Bayesian Inversion: Bayes Theorem, Prior Noise Models, Gaussian Approximations Sampling Methods | Noemi Petra, University of California, Merced |
Wednesday, August 10, 2016
Hamner Conference Center RTP
| Description | Speaker | Slides | Videos |
|---|---|---|---|
| “EM/MM Algorithms and their Modern Applications” | Hua Zhou, UCLA | ||
| Review of Nonlinear Optimization Algorithms | Hua Zhou, UCLA | ||
| Acceleration of EM/MM Algorithms; Parallel Computing with Julia Demonstration | Hua Zhou, UCLA |
Thursday, August 11, 2016
Hamner Conference Center RTP
| Description | Speaker | Slides | Videos |
|---|---|---|---|
| “Optimization for Statistics and Machine Learning” | Eric Chi, NCSU | ||
| Smooth Optimization | Eric Chi, NCSU | ||
| Non-smooth Optimization | Eric Chi, NCSU |
Friday, August 12, 2016
Hamner Conference Center RTP
| Description | Speaker | Slides | Videos |
|---|---|---|---|
| Lagrangian Duality and KKT Conditions | Eric Chi, NCSU | ||
| Lagrangian Duality and KKT Conditions (continued) | Eric Chi, NCSU | ||
| “Bayesian Tools for Optimization” | Vanja Dukic and David Bortz, University of Colorado |