Flows, Submodularity, Sparsity, and Beyond: Continuous Optimization Insights for Discrete Problems
In this thesis we build on connections between discrete and continuous optimization. In the first part of the thesis we propose faster second-order convex optimization algorithms for classical graph algorithmic problems. Our main contribution is to show that the runtime of interior point methods is...
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| Format: | Thesis |
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Massachusetts Institute of Technology
2023
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| Online Access: | https://hdl.handle.net/1721.1/147524 |