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Sophie Huiberts (CWI) will give a talk on Rising Stars – “Why can we solve (entire) linear programs? »- at the TCS Women Spotlight Workshop of STOC2021 on June 22, 2021. Inspirational speech by Professor Cynthia Dwork (Harvard University) – ‘Research. Results. Rejection. Redemption!’. Recommended!
On the TCS Women program website:
The workshop will include an inspiring talk by a senior researcher and short Rising Stars talks by senior graduate students and postdoctoral fellows. Registration for the workshop is free. Everyone is welcome.
- Date: June 22, 2021
- 9:00 a.m. – 11:00 a.m. (EDT): Rising Stars Lectures
- 11h00-12h00 (EDT): Inspirational speech Teacher. Cynthia Dwork (Title: Research. Results. Rejection. Redemption!)
- Rising Stars Lectures
- Arpita Biswas (Title: Fair allocation under matroid constraints)
- Prerona Chatterjee (Title: Lower limits in the complexity of algebraic circuits)
- Omrit Filter (Title: Proximity search in the trajectory data under the Fréchet distance)
- Sumegha Garg (Title: Confined space complexity of the room problem)
- Sophie Huiberts (Title: Why can we solve linear (integer) programs?)
- Sandra Kiefer (Title: Identifying graphics while playing with pebbles: how long does it take?)
- Audra McMillan (Title: Hiding Among the Clones: A Simple and Near-Optimal Analysis of Privacy Boost by Random Read)
About Sophie Huiberts from CWI:
Sophie huberts (CIO)
Title: Why can we solve linear (integer) programs?
Abstract: The algorithms commonly used to solve linear (integer) programs work surprisingly well. Theoretically, the practical performance of these decades-old algorithms is relatively poorly understood. In this talk, I will explain some difficulties in getting rigorous explanations, and I will describe recent work to go beyond the worst-case analysis for the simplex method for linear programming and the branch-and algorithm. -bound for integer programming.
Biography : Sophie Huiberts is a final year doctoral student at Centrum Wiskunde & Informatica (CWI), where she is advised by Daniel Dadush. His research interests focus on practical algorithms, polyhedra and combinatorial optimization.
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