Project: Network Algorithms and Distributed Optimization
We design and analyze approximation algorithms for NP-hard network optimization problems. These algorithms demonstrate the power of randomness for overcoming provably difficult tasks. Our theoretical results are supported by simulations to showcase their practicality. Recently, we have been investigating the application of reinforcement learning techniques to network optimization problems that include local restrictions.
Publications (2019 – Present)
Please find publications from prior to 2019 here.
Refereed Journal Papers
- Coming soon!
Refereed Conference Proceedings
- Improved Throughput for All-or-Nothing Multicommodity Flows with Arbitrary Demands. Anya Chaturvedi, Chandra Chekuri, Andréa W. Richa, Stefan Schmid, Matthias Rost, Jamison Weber. 39th International Symposium on Computer Performance, Modeling, Measurements and Evaluation, 2021.
- A Constant Approximation for Maximum Throughput Multicommodity Routing And Its Application to Delay-Tolerant Network Scheduling. Mengxue Liu, Andréa W. Richa, Matthias Rost, Stefan Schmid. IEEE Conference on Computer Communications (INFOCOM 2019), pp. 46-54, 2019.
Other Publications
- Coming soon!
Presentations
Invited Talks
- Coming soon!
Conference Talks
- Improved Throughput for All-or-Nothing Multicommodity Flows with Arbitrary Demands. Anya Chaturvedi, Jamison Weber. 39th International Symposium on Computer Performance, Modeling, Measurements and Evaluation, 2021.
Poster Presentations
- Coming soon!
Other Presentations
- Coming soon!
People
Current Team
Jamison Weber
PhD Student, Arizona State University[Website]
Anya Chaturvedi
Factory Automation Engineer, Intel[Website]
Funding
- Foundations of Emergent Computation and Self-Organized Adaptation. DoD MURI (Multidisciplinary University Research Initiative) Award #W911NF-19-1-0233. Feb. 2019 – Present.