Published September 2024
| Version Published
Journal Article
Open
Risk-Sensitive Online Algorithms
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1.
California Institute of Technology
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2.
University of Waterloo
Abstract
We study the design of risk-sensitive online algorithms, in which risk measures are used in the competitive analysis of randomized online algorithms.
Copyright and License
Copyright © 2024 Copyright is held by the owner/author(s).
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.
Acknowledgement
The authors acknowledge support from an NSF Graduate Research Fellowship (DGE-2139433), NSF Grants CNS-2146814, CPS-2136197, CNS-2106403, and NGSDI-2105648, the Resnick Sustainability Institute, and a Caltech S2I Grant.
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Additional details
Funding
- National Science Foundation
- DGE-2139433
- National Science Foundation
- CNS-2146814
- National Science Foundation
- CPS-2136197
- National Science Foundation
- CNS-2106403
- National Science Foundation
- NGSDI-2105648
- Resnick Sustainability Institute
- California Institute of Technology
Dates
- Available
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2024-09-06Published online