SIAM Student Chapter Seminar: Difference between revisions
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{| cellpadding="8" | {| cellpadding="8" | ||
!align="left" | date and time | !align="left" | date and time | ||
!align="left" | location | |||
!align="left" | speaker | !align="left" | speaker | ||
!align="left" | title | !align="left" | title | ||
|- | |- | ||
| Sept 20, 4 PM | | Sept 20, 4 PM | ||
| Ingraham 214 | |||
| [https://sites.google.com/view/julialindberg/home/ Julia Lindberg] (Electrical and Computer Engineering) | | [https://sites.google.com/view/julialindberg/home/ Julia Lindberg] (Electrical and Computer Engineering) | ||
|''[[#Sept 20, Julia Lindberg (Electrical and Computer Engineering)|Polynomial system solving in applications]]'' | |''[[#Sept 20, Julia Lindberg (Electrical and Computer Engineering)|Polynomial system solving in applications]]'' | ||
Revision as of 22:44, 15 September 2021
- When: Typically 4 PM
- Where: TBA
- Organizers: Evan Sorensen
- Faculty advisers: Jean-Luc Thiffeault, Steve Wright
- To join the SIAM Chapter mailing list: email siam-chapter+join@g-groups.wisc.edu.
Fall 2021
| date and time | location | speaker | title |
|---|---|---|---|
| Sept 20, 4 PM | Ingraham 214 | Julia Lindberg (Electrical and Computer Engineering) | Polynomial system solving in applications |
| Sept 27, 4 PM, Zoom talk | William Cocke (US Army) | ||
| Oct 4, 2:45 PM | Anjali Nair (Math) | ||
| Oct 11, 4 PM, Zoom talk | Kurt Ehlert (Trading Strategy Developer at Auros) | ||
| Oct 18, 4 PM | Jason Tochinsky (Math) | ||
| Oct 25, 4 PM, Zoom talk | Patrick Bardsley (Machine Learning Engineer at Cirrus Logic) | ||
| Nov 8, 4 PM, Zoom talk | Liban Mohammed(Machine Learning Engineer at MITRE) | ||
| Dec 6, 4 PM | Hongxu Chen(Math) |
Abstracts
Sept 20, Julia Lindberg (Electrical and Computer Engineering)
Polynomial systems arise naturally in many applications in engineering and the sciences. This talk will outline classes of homotopy continuation algorithms used to solve them. I will then describe ways in which structures such as irreducibility, symmetry and sparsity can be used to improve computational speed. The efficacy of these algorithms will be demonstrated on systems in power systems engineering, statistics and optimization