Srinivasan Arunachalam
Srinivasan Arunachalam
Postdoc, MIT
Verified email at mit.edu - Homepage
TitleCited byYear
Is absolute separability determined by the partial transpose?
S Arunachalam, N Johnston, V Russo
Quantum Information & Computation 15 (7&8), 694-720, 2015
242015
Guest column: a survey of quantum learning theory
S Arunachalam, R de Wolf
ACM SIGACT News 48 (2), 41-67, 2017
17*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
172015
Optimal quantum sample complexity of learning algorithms
S Arunachalam, R de Wolf
arXiv preprint arXiv:1607.00932, 2016
162016
Optimizing quantum optimization algorithms via faster quantum gradient computation
A Gilyén, S Arunachalam, N Wiebe
arXiv preprint arXiv:1711.00465, 2017
42017
Quantum query algorithms are completely bounded forms
S Arunachalam, J Briët, C Palazuelos
arXiv preprint arXiv:1711.07285, 2017
32017
Quantum speed-ups for boolean satisfiability and derivative-free optimization
S Arunachalam
University of Waterloo, 2014
32014
Quantum hedging in two-round prover-verifier interactions
S Arunachalam, A Molina, V Russo
arXiv preprint arXiv:1310.7954, 2013
32013
Improved bounds on Fourier entropy and Min-entropy
S Arunachalam, S Chakraborty, M Koucký, N Saurabh, R de Wolf
arXiv preprint arXiv:1809.09819, 2018
12018
Optimizing the number of gates in quantum search
S Arunachalam, R De Wolf
arXiv preprint arXiv:1512.07550, 2015
12015
Satisfiability through auto correlation
S Arunachalam, I Kotsireas
SAT competition, 2014
12014
Two new results about quantum exact learning
S Arunachalam, S Chakraborty, T Lee, R de Wolf
arXiv preprint arXiv:1810.00481, 2018
2018
Quantum algorithms and learning theory
S Arunachalam
2018
A Substitution to Bernoulli Numbers in easier computation of (\zeta (2k))
S Arunachalam
arXiv preprint arXiv:1105.1214, 2011
2011
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Articles 1–14