Romina Yalovetzky

12 papers A* 1A 1Journal 10
YearRankTypeTitle / Venue / Authors
2025 J jnl
A Unified Framework for Provably Efficient Algorithms to Estimate Shapley Values.
CoRR
Tyler Chen, Akshay Seshadri, Mattia J. Villani, Pradeep Niroula, Shouvanik Chakrabarti, Archan Ray, Pranav Deshpande, Romina Yalovetzky, Marco Pistoia, Niraj Kumar
2025 J jnl
Des-q: a quantum algorithm to provably speedup retraining of decision trees.
Quantum
Niraj Kumar, Romina Yalovetzky, Changhao Li, Pierre Minssen, Marco Pistoia
2024 A* conf
Invited: Challenges and Opportunities of Quantum Optimization in Finance.
DAC
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
2024 J jnl
Prospects of Privacy Advantage in Quantum Machine Learning.
CoRR
Jamie Heredge, Niraj Kumar, Dylan Herman, Shouvanik Chakrabarti, Romina Yalovetzky, Shree Hari Sureshbabu, Changhao Li, Marco Pistoia
2024 J jnl
QC-Forest: a Classical-Quantum Algorithm to Provably Speedup Retraining of Random Forest.
CoRR
Romina Yalovetzky, Niraj Kumar, Changhao Li, Marco Pistoia
2023 J jnl
Des-q: a quantum algorithm to construct and efficiently retrain decision trees for regression and binary classification.
CoRR
Niraj Kumar, Romina Yalovetzky, Changhao Li, Pierre Minssen, Marco Pistoia
2023 J jnl
Evidence of Scaling Advantage for the Quantum Approximate Optimization Algorithm on a Classically Intractable Problem.
CoRR
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
2023 J jnl
Quantum Deep Hedging.
CoRR
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
2023 J jnl
Quantum Deep Hedging.
Quantum
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
2022 J jnl
Constrained Quantum Optimization for Extractive Summarization on a Trapped-ion Quantum Computer.
CoRR
Pradeep Niroula, Ruslan Shaydulin, Romina Yalovetzky, Pierre Minssen, Dylan Herman, Shaohan Hu, Marco Pistoia
2021 A conf
Quantum Machine Learning for Finance ICCAD Special Session Paper.
ICCAD
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
2021 J jnl
Quantum Machine Learning for Finance.
CoRR
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