Srinivasan Arunachalam

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Ronald de WolfCWI and University of AmsterdamVerified email at cwi.nl
Sourav ChakrabortyIndian Statistical Institute, KolkataVerified email at isical.ac.in
Kristan TemmeIBM T.J. Watson ResearchVerified email at ibm.com
András GilyénMarie Curie fellow, Alfréd Rényi Institute of MathematicsVerified email at renyi.hu
Nathan WiebeUniversity of TorontoVerified email at uw.edu
Vincent RussoISARAVerified email at uwaterloo.ca
Anurag AnshuHarvard UniversityVerified email at g.harvard.edu
Alex Bredariol GriloCNRS, LIP6, Sorbonne UniversitéVerified email at sorbonne-universite.fr
Yunchao LiuGraduate Student, UC BerkeleyVerified email at berkeley.edu
Priyaa Varshinee SrinivasanPh.D Student, University of CalgaryVerified email at ucalgary.ca
Vlad GheorghiuInstitute for Quantum Computing, University of Waterloo, CanadaVerified email at uwaterloo.ca
Tomas Jochym-O'ConnorIBM ResearchVerified email at ibm.com
Nathaniel JohnstonMount Allison UniversityVerified email at mta.ca
Nitin SaurabhTechnion - IITVerified email at cs.technion.ac.il
Aarthi SundaramResearcher, MicrosoftVerified email at microsoft.com
Troy LeeUniversity of Technology SydneyVerified email at uts.edu.au
Carlos PalazuelosUniversidad Complutense de Madrid, SpainVerified email at mat.ucm.es
Jop BriëtCWIVerified email at cwi.nl
John A. SmolinIBM ResearchVerified email at alum.mit.edu
Yihui QuekStanford University and Free University of BerlinVerified email at stanford.edu

Srinivasan Arunachalam

IBM T. J. Watson Research Center

Verified email at ibm.com - Homepage

Quantum computing complexity theory learning theory Boolean function analysis


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Guest column: A survey of quantum learning theory S Arunachalam, R de Wolf ACM SIGACT News 48 (2), 41-67, 2017	127	2017
A rigorous and robust quantum speed-up in supervised machine learning Y Liu, S Arunachalam, K Temme Nature Physics 17 (9), 1013-1017, 2021	110	2021
On the robustness of bucket brigade quantum RAM S Arunachalam, V Gheorghiu, T Jochym-O’Connor, M Mosca, ... New Journal of Physics 17 (12), 123010, 2015	100	2015
Optimizing quantum optimization algorithms via faster quantum gradient computation A Gilyén, S Arunachalam, N Wiebe Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete …, 2019	84	2019
Optimal quantum sample complexity of learning algorithms S Arunachalam, R De Wolf The Journal of Machine Learning Research 19 (1), 2879-2878, 2018	70	2018
Sample-efficient learning of interacting quantum systems A Anshu, S Arunachalam, T Kuwahara, M Soleimanifar Nature Physics 17 (8), 931-935, 2021	34*	2021
Is absolute separability determined by the partial transpose? S Arunachalam, N Johnston, V Russo Quantum Information & Computation 15 (7-8), 694-720, 2014	29*	2014
Quantum query algorithms are completely bounded forms S Arunachalam, J Briët, C Palazuelos SIAM Journal on Computing 48 (3), 903-925, 2019	23	2019
Two new results about quantum exact learning S Arunachalam, S Chakraborty, T Lee, M Paraashar, R de Wolf Quantum 5, 587, 2021	19	2021
Quantum statistical query learning S Arunachalam, AB Grilo, H Yuen arXiv preprint arXiv:2002.08240, 2020	16	2020
Improved Bounds on Fourier Entropy and Min-entropy S Arunachalam, S Chakraborty, M Koucký, N Saurabh, R De Wolf ACM Transactions on Computation Theory (TOCT) 13 (4), 1-40, 2021	14	2021
Quantum boosting S Arunachalam, R Maity International Conference on Machine Learning, 377-387, 2020	12	2020
Quantum hardness of learning shallow classical circuits S Arunachalam, AB Grilo, A Sundaram SIAM Journal on Computing 50 (3), 972-1013, 2021	10	2021
Simpler (classical) and faster (quantum) algorithms for gibbs partition functions S Arunachalam, V Havlicek, G Nannicini, K Temme, P Wocjan 2021 IEEE International Conference on Quantum Computing and Engineering (QCE …, 2021	8	2021
Quantum coupon collector S Arunachalam, A Belovs, AM Childs, R Kothari, A Rosmanis, R de Wolf arXiv preprint arXiv:2002.07688, 2020	8	2020
Optimizing the number of gates in quantum search S Arunachalam, R De Wolf arXiv preprint arXiv:1512.07550, 2015	8	2015
Quantum hedging in two-round prover-verifier interactions S Arunachalam, A Molina, V Russo arXiv preprint arXiv:1310.7954, 2013	8	2013
Private learning implies quantum stability S Arunachalam, Y Quek, J Smolin Advances in Neural Information Processing Systems 34, 2021	7	2021
Quantum speed-ups for Boolean satisfiability and derivative-free optimization/by Srinivasan Arunachalam. S Arunachalam University of Waterloo, Waterloo, Ontario, Canada, 2014	6*	2014
Quantum learning algorithms imply circuit lower bounds S Arunachalam, AB Grilo, T Gur, IC Oliveira, A Sundaram 2021 IEEE 62nd Annual Symposium on Foundations of Computer Science (FOCS …, 2022	3	2022

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