Niraj Kumar - RankMe

28 papers A* 1Journal 27

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Numerical Gradient Inversion Attack in Variational Quantum Neural-Networks. CoRR Georgios Papadopoulos, Shaltiel Eloul, Yash Satsangi, Jamie Heredge, Niraj Kumar, Chun-Fu Chen, Marco Pistoia
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`	A simple analysis of a quantum-inspired algorithm for solving low-rank linear systems. CoRR Tyler Chen, Junhyung Lyle Kim, Archan Ray, Shouvanik Chakrabarti, Dylan Herman, Niraj Kumar
2025	J	`jnl`	Applications of Certified Randomness. CoRR Omar Amer, Shouvanik Chakrabarti, Kaushik Chakraborty, Shaltiel Eloul, Niraj Kumar, Charles Lim, Minzhao Liu, Pradeep Niroula, Yash Satsangi, Ruslan Shaydulin, Marco Pistoia
2025	J	`jnl`	Certified randomness using a trapped-ion quantum processor. CoRR Minzhao Liu, Ruslan Shaydulin, Pradeep Niroula, Matthew DeCross, Shih-Han Hung, Wen Yu Kon, Enrique Cervero Martín, Kaushik Chakraborty, Omar Amer, Scott Aaronson, Atithi Acharya, Yuri Alexeev, K. Jordan Berg, Shouvanik Chakrabarti, Florian J. Curchod, Joan M. Dreiling, Neal Erickson, Cameron Foltz, Michael Foss-Feig, David Hayes, Travis S. Humble, Niraj Kumar, Jeffrey Larson, Danylo Lykov, Michael Mills, Steven A. Moses, Brian Neyenhuis, Shaltiel Eloul, Peter Siegfried, James Walker, Charles Lim, Marco Pistoia
2025	J	`jnl`	Certified randomness using a trapped-ion quantum processor. Nat. Minzhao Liu, Ruslan Shaydulin, Pradeep Niroula, Matthew DeCross, Shih-Han Hung, Wen Yu Kon, Enrique Cervero Martín, Kaushik Chakraborty, Omar Amer, Scott Aaronson, Atithi Acharya, Yuri Alexeev, K. Jordan Berg, Shouvanik Chakrabarti, Florian J. Curchod, Joan M. Dreiling, Neal Erickson, Cameron Foltz, Michael Foss-Feig, David Hayes, Travis S. Humble, Niraj Kumar, Jeffrey Larson, Danylo Lykov, Michael Mills, Steven A. Moses, Brian Neyenhuis, Shaltiel Eloul, Peter Siegfried, James Walker, Charles Lim, Marco Pistoia
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
2025	J	`jnl`	GPU-Parallelizable Randomized Sketch-and-Precondition for Linear Regression using Sparse Sign Sketches. CoRR Tyler Chen, Pradeep Niroula, Archan Ray, Pragna Subrahmanya, Marco Pistoia, Niraj Kumar
2025	J	`jnl`	MetaTT: A Global Tensor-Train Adapter for Parameter-Efficient Fine-Tuning. CoRR Javier Lopez-Piqueres, Pranav Deshpande, Archan Ray, Mattia J. Villani, Marco Pistoia, Niraj Kumar
2025	J	`jnl`	New Improvements in Solving Large LABS Instances Using Massively Parallelizable Memetic Tabu Search. CoRR Zhiwei Zhang, Jiayu Shen, Niraj Kumar, Marco Pistoia
2025	J	`jnl`	Provably faster randomized and quantum algorithms for k-means clustering via uniform sampling. CoRR Tyler Chen, Archan Ray, Akshay Seshadri, Dylan Herman, Bao Bach, Pranav Deshpande, Abhishek Som, Niraj Kumar, 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`	Blind quantum machine learning with quantum bipartite correlator. CoRR Changhao Li, Boning Li, Omar Amer, Ruslan Shaydulin, Shouvanik Chakrabarti, Guoqing Wang, Haowei Xu, Hao Tang, Isidor Schoch, Niraj Kumar, Charles Lim, Ju Li, Paola Cappellaro, 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`	Expressive variational quantum circuits provide inherent privacy in federated learning. CoRR Niraj Kumar, Jamie Heredge, Changhao Li, Shaltiel Eloul, Shree Hari Sureshbabu, Marco Pistoia
2023	J	`jnl`	Privacy-preserving quantum federated learning via gradient hiding. CoRR Changhao Li, Niraj Kumar, Zhixin Song, Shouvanik Chakrabarti, Marco Pistoia
2023	J	`jnl`	Variational quantum algorithm for unconstrained black box binary optimization: Application to feature selection. Quantum Christa Zoufal, Ryan V. Mishmash, Nitin Sharma, Niraj Kumar, Aashish Sheshadri, Amol Deshmukh, Noelle Ibrahim, Julien Gacon, Stefan Woerner
2022	J	`jnl`	Graph neural network initialisation of quantum approximate optimisation. Quantum Nishant Jain, Brian Coyle, Elham Kashefi, Niraj Kumar
2021	J	`jnl`	Client-server Identification Protocols with Quantum PUF. ACM Trans. Quantum Comput. Mina Doosti, Niraj Kumar, Mahshid Delavar, Elham Kashefi
2021	J	`jnl`	Graph neural network initialisation of quantum approximate optimisation. CoRR Nishant Jain, Brian Coyle, Elham Kashefi, Niraj Kumar
2021	J	`jnl`	On the Connection Between Quantum Pseudorandomness and Quantum Hardware Assumptions. CoRR Mina Doosti, Niraj Kumar, Elham Kashefi, Kaushik Chakraborty
2020	J	`jnl`	Client-Server Identification Protocols with Quantum PUF. CoRR Mina Doosti, Niraj Kumar, Mahshid Delavar, Elham Kashefi
2020	J	`jnl`	Quantum versus Classical Generative Modelling in Finance. CoRR Brian Coyle, Maxwell Henderson, Justin Chan Jin Le, Niraj Kumar, Marco Paini, Elham Kashefi
2020	J	`jnl`	Variational Quantum Cloning: Improving Practicality for Quantum Cryptanalysis. CoRR Brian Coyle, Mina Doosti, Elham Kashefi, Niraj Kumar
2019	J	`jnl`	Practically Feasible Robust Quantum Money with Classical Verification. Cryptogr. Niraj Kumar