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In keeping with the tradition of the last twenty-some years, the Readings in Optimization seminar will focus on an advanced topic of interest to a portion of the MIT optimization community: randomized methods for deterministic optimization
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English [CC]
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Description
In contrast to conventional optimization algorithms whose iterates are computed and analyzed deterministically, randomized methods rely on stochastic processes and random number/vector generation as part of the algorithm and/or its analysis. In the seminar, we will study some very recent papers on this topic, many by MIT faculty, as well as some older papers from the existing literature that are only now receiving attention.
Course content
- Presentation courtesy of Rob Freund Unlimited
- Presentation courtesy of David Craft Unlimited
- Presentation courtesy of Susan Martonosi Unlimited
- Presentation courtesy of Jan De Mot Unlimited
- Both presentations courtesy of Dan Stratila Unlimited
- Presentation courtesy of Michele Aghassi Unlimited
- Presentation courtesy of Michael Yee Unlimited
- Presentation courtesy of Michael Yee and Kwong-Meng Teo Unlimited
Instructor
Massachusetts Institute of Technology
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