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Shouvanik Chakrabarti
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2019
T. Li
,
Chakrabarti, S.
, and
Wu, X.
,
“
Sublinear quantum algorithms for training linear and kernel-based classifiers
”
,
Proceedings of the 36th International Conference on Machine Learning (ICML 2019) PMLR
, vol. 97, pp. 3815-3824, 2019.
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S. Chakrabarti
,
Huang, Y.
,
Li, T.
,
Feizi, S.
, and
Wu, X.
,
“
Quantum Wasserstein Generative Adversarial Networks
”
,
Advances in Neural Information Processing Systems (NIPS)
, vol. 32, 2019.
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2020
T. Li
,
Wang, C.
,
Chakrabarti, S.
, and
Wu, X.
,
“
Sublinear classical and quantum algorithms for general matrix games
”
,
To appear in the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2021)
, 2020.
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S. Chakrabarti
,
Childs, A. M.
,
Li, T.
, and
Wu, X.
,
“
Quantum algorithms and lower bounds for convex optimization
”
,
Quantum
, vol. 4, no. 221, 2020.
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S. Zhu
,
Hung, S. - H.
,
Chakrabarti, S.
, and
Wu, X.
,
“
On the Principles of Differentiable Quantum Programming Languages
”
, 2020.
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2021
S. Chakrabarti
,
Krishnakumar, R.
,
Mazzola, G.
,
Stamatopoulos, N.
,
Woerner, S.
, and
Zeng, W. J.
,
“
A Threshold for Quantum Advantage in Derivative Pricing
”
,
Quantum
, vol. 5, p. 463, 2021.
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M. Pistoia
,
Ahmad, S. Farhan
,
Ajagekar, A.
,
Buts, A.
,
Chakrabarti, S.
,
Herman, D.
,
Hu, S.
,
Jena, A.
,
Minssen, P.
,
Niroula, P.
,
Rattew, A.
,
Sun, Y.
, and
Yalovetzky, R.
,
“
Quantum Machine Learning for Finance
”
, 2021.
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2022
X. You
,
Chakrabarti, S.
, and
Wu, X.
,
“
A Convergence Theory for Over-parameterized Variational Quantum Eigensolvers
”
, 2022.
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2023
X. You
,
Chakrabarti, S.
,
Chen, B.
, and
Wu, X.
,
“
Analyzing Convergence in Quantum Neural Networks: Deviations from Neural Tangent Kernels
”
, 2023.
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S. Chakrabarti
,
Childs, A. M.
,
Hung, S. - H.
,
Li, T.
,
Wang, C.
, and
Wu, X.
,
“
Quantum algorithm for estimating volumes of convex bodies
”
,
ACM Transactions on Quantum Computing
, vol. 4, 2023.
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