Information Complexity of Convex Mixed-Integer Optimization (follow up work), with Amitabh Basu, Hongyi Jiang, and Marco Molinaro.
Quantum-Accelerated Distributed Graph Algorithms, with Dr. David Bernal Neira and Dr. Eleanor Rieffel from NASA's QuAIL group.
Nonstandard Boltzmann Machine architectures for larger implementations in quantum annealers. I haven't had much time to work on this project lately but believe it is promising -- if you are interested in collaborating on this, please reach out!
Kerger, Molinaro, Jiang, Basu 2024. A Universal Transfer Theorem for Convex Opti-
mization Algorithms Using Inexact First-order Oracles. Submitted to ICML 2024, in review.
Kerger, Miyazaki 2023. Quantum Image Denoising: A Framework via Boltzmann Machines, QUBO, and Quantum Annealing. Published in Frontiers in Theoretical Computer Science's "Experience in Quantum Annealing" research topic,
2023, available here. Arxiv preprint available.
Kerger, Bernal Neira, Gonzalez Izquierdo, Rieffel 2023. Mind the O-tilde: Asymptotically Better, but Still Impractical, Quantum Distributed Algorithms.
Published in Algorithms, 2023, available here. Arxiv preprint available.
Basu, Jiang, Kerger, Molinaro, * 2023. Information Complexity of Mixed-Integer Convex Optimization, IPCO 2023 proceedings. Available here.
Quantum Image Denoising: A Framework with Boltzmann Machines, QUBO, and Quantum
Annealing, Fordham Uniersity Math Department Seminar, October 18, 2023.
Information Complexity of Convex MIP: Different Oracle Settings and Transfers between them Cornell young researchers' workshop, October 3, 2023.
Quantum Distributed Algorithms for Approximate Steiner Trees and Directed Minimum Span-
ning Trees. IEEE Quantum Week 2023, Seattle WA, September 21, 2023.
Information Complexity Under Different Oracle Settings, Johns Hopkins University, Baltimore MD. Applied Math and Statistics PhD Seminar Series, September 12, 2023. Slides available here
Quantum Image Denoising: A Framework with Boltzmann Machines, QUBO, and Quantum Annealing, NASA Quantum Artificial Intelligence Laboratory. AUgust 31, 2023.
Complexity of Mixed-Integer Convex Optimization, IPCO 2023, Madison WI. June 25, 2023. Slides available here
Algorithms in Distributed Quantum Computing Under Limited Communication: Faster Asymptotic Algorithms, Impracticality, and Takeaways, Workshop for Quantum and Hybrid Quantum-Classical Computing, ISC-HPC 2023, May 25 2023, Hamburg Germany.
Distributed Quantum Computing Johns Hopkins University, Baltimore MD. Applied Math and Statistics PhD Seminar Series, March 7, 2023.
Quantum-Accelerated Distributed Algorithms for Approximate Steiner Trees and Directed Minimum Spanning Trees. Workshop on Quantum Computing and Operations research,
The Fields Institute, Toronto, Canada. Poster available through here.
Image denoising via Quadratic Binary Optimization. Johns Hopkins University, Baltimore MD. Applied Math and Statistics MSE Seminar Series, October 5, 2022.
An Introduction to Quantum Computing and Grover's Search Algorithm. Johns Hopkins University, Baltimore MD. Applied Math and Statistics PhD Seminar Series, September 28, 2022.
Quantum-Accelerated Distributed Graph Algorithms. NASA Ames Quantum AI Lab, Mountain View CA. QuAIL Group Meeting, September 2, 2022.
Boltzmann Machine Learning with Annealing on SX-Aurora TSUBASA. Tohoku University, Sendai, Japan. GRIPS Research Symposium, July 14, 2022.
Image Denoising with Quantum Annealing via Boltzmann Machines. Johns Hopkins University, Baltimore MD. Applied Math and Statistics PhD Seminar Series, April 26, 2022.