Dylan Herman

According to our database, Dylan Herman authored at least 19 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Quantum Speedups for Group Relaxations of Integer Linear Programs.

Brandon Augustino, Dylan Herman, Guneykan Ozgul, Jacob Watkins, Atithi Acharya, Enrico Fontana, Junhyung Lyle Kim, Shouvanik Chakrabarti

CoRR, February, 2026

Quantum Speedups for Derivative Pricing Beyond Black-Scholes.

Dylan Herman, Yue Sun, Jin-Peng Liu, Marco Pistoia, Charlie C. L. Wang, Rob Otter, Shouvanik Chakrabarti, Aram W. Harrow

CoRR, February, 2026

2025

Mechanisms for Quantum Advantage in Global Optimization of Nonconvex Functions.

Dylan Herman, Guneykan Ozgul, Anuj Apte, Junhyung Lyle Kim, Anupam Prakash, Jiayu Shen, Shouvanik Chakrabarti

CoRR, October, 2025

A simple analysis of a quantum-inspired algorithm for solving low-rank linear systems.

Tyler Chen, Junhyung Lyle Kim, Archan Ray, Shouvanik Chakrabarti, Dylan Herman, Niraj Kumar

CoRR, August, 2025

Provably faster randomized and quantum algorithms for k-means clustering via uniform sampling.

Tyler Chen, Archan Ray, Akshay Seshadri, Dylan Herman, Bao Bach, Pranav Deshpande, Abhishek Som, Niraj Kumar, Marco Pistoia

CoRR, April, 2025

Iterative Interpolation Schedules for Quantum Approximate Optimization Algorithm.

Anuj Apte, Shree Hari Sureshbabu, Ruslan Shaydulin, Sami Boulebnane, Zichang He, Dylan Herman, James Sud, Marco Pistoia

CoRR, April, 2025

On Speedups for Convex Optimization via Quantum Dynamics.

Shouvanik Chakrabarti, Dylan Herman, Jacob Watkins, Enrico Fontana, Brandon Augustino, Junhyung Lyle Kim, Marco Pistoia

CoRR, March, 2025

2024

Parameter Setting in Quantum Approximate Optimization of Weighted Problems.

Shree Hari Sureshbabu, Dylan Herman, Ruslan Shaydulin, Joao Basso, Shouvanik Chakrabarti, Yue Sun, Marco Pistoia

Quantum, January, 2024

Generalized Short Path Algorithms: Towards Super-Quadratic Speedup over Markov Chain Search for Combinatorial Optimization.

Shouvanik Chakrabarti, Dylan Herman, Guneykan Ozgul, Shuchen Zhu, Brandon Augustino, Tianyi Hao, Zichang He, Ruslan Shaydulin, Marco Pistoia

CoRR, 2024

Prospects of Privacy Advantage in Quantum Machine Learning.

Jamie Heredge, Niraj Kumar, Dylan Herman, Shouvanik Chakrabarti, Romina Yalovetzky, Shree Hari Sureshbabu, Changhao Li, Marco Pistoia

CoRR, 2024

Parameter Setting Heuristics Make the Quantum Approximate Optimization Algorithm Suitable for the Early Fault-Tolerant Era.

Zichang He, Ruslan Shaydulin, Dylan Herman, Changhao Li, Rudy Raymond, Shree Hari Sureshbabu, Marco Pistoia

Proceedings of the 43rd IEEE/ACM International Conference on Computer-Aided Design, 2024

Invited: Challenges and Opportunities of Quantum Optimization in Finance.

Zichang He, Shouvanik Chakrabarti, Dylan Herman, Niraj Kumar, Changhao Li, Pierre Minssen, Pradeep Niroula, Ruslan Shaydulin, Yue Sun, Shree Hari Sureshbabu, Romina Yalovetzky, Marco Pistoia

Proceedings of the 61st ACM/IEEE Design Automation Conference, 2024

2023

Quantum Deep Hedging.

El Amine Cherrat, Snehal Raj, Iordanis Kerenidis, Abhishek Shekhar, Ben Wood, Jon Dee, Shouvanik Chakrabarti, Chun-Fu Richard Chen, Dylan Herman, Shaohan Hu, Pierre Minssen, Ruslan Shaydulin, Yue Sun, Romina Yalovetzky, Marco Pistoia

Quantum, November, 2023

Code from "Evidence of Scaling Advantage for the Quantum Approximate Optimization Algorithm on a Classically Intractable Problem".

Ruslan Shaydulin, Changhao Li, Shouvanik Chakrabarti, Matthew DeCross, Dylan Herman, Niraj Kumar, Jeffrey Larson, Danylo Lykov, Pierre Minssen, Yue Sun, Yuri Alexeev, Joan M. Dreiling, John P. Gaebler, Thomas M. Gatterman, Justin A. Gerber, Kevin Gilmore, Dan Gresh, Nathan Hewitt, Chandler V. Horst, Shaohan Hu, Jacob Johansen, Mitchell Matheny, Tanner Mengle, Michael Mills, Steven A. Moses, Brian Neyenhuis, Peter Siegfried, Romina Yalovetzky, Marco Pistoia

Dataset, August, 2023

Evidence of Scaling Advantage for the Quantum Approximate Optimization Algorithm on a Classically Intractable Problem.

Ruslan Shaydulin, Changhao Li, Shouvanik Chakrabarti, Matthew DeCross, Dylan Herman, Niraj Kumar, Jeffrey Larson, Danylo Lykov, Pierre Minssen, Yue Sun, Yuri Alexeev, Joan M. Dreiling, John P. Gaebler, Thomas M. Gatterman, Justin A. Gerber, Kevin Gilmore, Dan Gresh, Nathan Hewitt, Chandler V. Horst, Shaohan Hu, Jacob Johansen, Mitchell Matheny, Tanner Mengle, Michael Mills, Steven A. Moses, Brian Neyenhuis, Peter Siegfried, Romina Yalovetzky, Marco Pistoia

CoRR, 2023

Alignment between Initial State and Mixer Improves QAOA Performance for Constrained Portfolio Optimization.

Zichang He, Ruslan Shaydulin, Shouvanik Chakrabarti, Dylan Herman, Changhao Li, Yue Sun, Marco Pistoia

CoRR, 2023

2022

Constrained Quantum Optimization for Extractive Summarization on a Trapped-ion Quantum Computer.

Pradeep Niroula, Ruslan Shaydulin, Romina Yalovetzky, Pierre Minssen, Dylan Herman, Shaohan Hu, Marco Pistoia

CoRR, 2022

2021

Quantum Machine Learning for Finance.

Marco Pistoia, Syed Farhan Ahmad, Akshay Ajagekar, Alexander Buts, Shouvanik Chakrabarti, Dylan Herman, Shaohan Hu, Andrew Jena, Pierre Minssen, Pradeep Niroula, Arthur G. Rattew, Yue Sun, Romina Yalovetzky

CoRR, 2021

Quantum Machine Learning for Finance ICCAD Special Session Paper.

Marco Pistoia, Syed Farhan Ahmad, Akshay Ajagekar, Alexander Buts, Shouvanik Chakrabarti, Dylan Herman, Shaohan Hu, Andrew Jena, Pierre Minssen, Pradeep Niroula, Arthur G. Rattew, Yue Sun, Romina Yalovetzky

Proceedings of the IEEE/ACM International Conference On Computer Aided Design, 2021