Srinivasan Arunachalam
Srinivasan Arunachalam
IBM Quantum, Almaden Research Center
Verified email at - Homepage
Cited by
Cited by
A rigorous and robust quantum speed-up in supervised machine learning
Y Liu, S Arunachalam, K Temme
Nature Physics 17 (9), 1013-1017, 2021
Guest column: A survey of quantum learning theory
S Arunachalam, R de Wolf
ACM Sigact News 48 (2), 41-67, 2017
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
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
Optimal quantum sample complexity of learning algorithms
S Arunachalam, R De Wolf
The Journal of Machine Learning Research 19 (1), 2879-2878, 2018
Sample-efficient learning of interacting quantum systems
A Anshu, S Arunachalam, T Kuwahara, M Soleimanifar
Nature Physics 17 (8), 931-935, 2021
Quantum query algorithms are completely bounded forms
S Arunachalam, J Briët, C Palazuelos
SIAM Journal on Computing 48 (3), 903-925, 2019
Is absolute separability determined by the partial transpose?
S Arunachalam, N Johnston, V Russo
Quantum Information & Computation 15 (7-8), 694-720, 2014
Two new results about quantum exact learning
S Arunachalam, S Chakraborty, T Lee, M Paraashar, R de Wolf
Quantum 5, 587, 2021
Quantum boosting
S Arunachalam, R Maity
International Conference on Machine Learning, 377-387, 2020
Quantum statistical query learning
S Arunachalam, AB Grilo, H Yuen
arXiv preprint arXiv:2002.08240, 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
Quantum hardness of learning shallow classical circuits
S Arunachalam, AB Grilo, A Sundaram
SIAM Journal on Computing 50 (3), 972-1013, 2021
Optimizing the number of gates in quantum search
S Arunachalam, R De Wolf
arXiv preprint arXiv:1512.07550, 2015
Simpler (classical) and faster (quantum) algorithms for Gibbs partition functions
S Arunachalam, V Havlicek, G Nannicini, K Temme, P Wocjan
Quantum 6, 789, 2022
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
Private learning implies quantum stability
S Arunachalam, Y Quek, J Smolin
Advances in Neural Information Processing Systems 34, 2021
Quantum coupon collector
S Arunachalam, A Belovs, AM Childs, R Kothari, A Rosmanis, R De Wolf
arXiv preprint arXiv:2002.07688, 2020
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
Quantum hedging in two-round prover-verifier interactions
S Arunachalam, A Molina, V Russo
arXiv preprint arXiv:1310.7954, 2013
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