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Journal Article
K. Hietala, Rand, R., Hung, S. - H., Wu, X., and Hicks, M., A Verified Optimizer for Quantum Circuits, Proceedings of the ACM on Programming Languages, vol. 5, no. POPL, 2021.
K. Hietala, Rand, R., Hung, S. - H., Wu, X., and Hicks, M., Verified Optimization in a Quantum Intermediate Representation, 2019.
L. Li, Voichick, F., Hietala, K., Peng, Y., Wu, X., and Hicks, M., Verified Compilation of Quantum Oracles, 2021.
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.
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.
T. Peng, Harrow, A., Ozols, M., and Wu, X., Simulating large quantum circuits on a small quantum computer, Phys. Rev. Lett., vol. 125, no. 150504, 2020.
X. Wu, Yao, P., and Yuen, H., Raz-McKenzie simulation with the inner product gadget, Electronic Colloquium on Computational Complexity (ECCC), 2017.
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.
F. G. S. L. Brandão, Kalev, A., Li, T., Lin, C. Yen- Yu, Svore, K. M., and Wu, X., Quantum SDP Solvers: Large Speed-ups, Optimality, and Applications to Quantum Learning, To appear at the 46th International Colloquium on Automata, Languages and Programming (ICALP 2019), 2018.
T. Li and Wu, X., Quantum query complexity of entropy estimation, IEEE Transactions on Information Theory, vol. 65, no. 5, pp. 2899-2921, 2019.
S. Chakrabarti, Childs, A. M., Li, T., and Wu, X., Quantum algorithms and lower bounds for convex optimization, Quantum, vol. 4, no. 221, 2020.
S. Chakrabarti, Childs, A. M., Hung, S. - H., Li, T., Wang, C., and Wu, X., Quantum algorithm for estimating volumes of convex bodies, 2019.
S. - H. Hung, Hietala, K., Zhu, S., Ying, M., Hicks, M., and Wu, X., Quantitative Robustness Analysis of Quantum Programs (Extended Version), Proc. ACM Program. Lang., vol. 3, no. POPL, p. Article 31, 2018.
S. Zhu, Hung, S. - H., Chakrabarti, S., and Wu, X., On the Principles of Differentiable Quantum Programming Languages, 2020.
A. W. Harrow, Natarajan, A., and Wu, X., Limitations of semidefinite programs for separable states and entangled games, Commun. Math. Phys., vol. 366, no. 2, 2019.
X. You and Wu, X., Exponentially Many Local Minima in Quantum Neural Networks, Proceedings of the 38th International Conference on Machine Learning, PMLR, vol. 139, pp. 12144-12155, 2021.
F. G. S. L. Brandão, Kalev, A., Li, T., Lin, C. Yen- Yu, Svore, K. M., and Wu, X., Exponential Quantum Speed-ups for Semidefinite Programming with Applications to Quantum Learning, 2017.
M. Barbosa, Barthe, G., Fan, X., Grégoire, B., Hung, S. - H., Katz, J., Strub, P. - Y., Wu, X., and Zhou, L., EasyPQC: Verifying Post-Quantum Cryptography, ACM CCS 2021, 2021.
X. You, Chakrabarti, S., and Wu, X., A Convergence Theory for Over-parameterized Variational Quantum Eigensolvers, 2022.
K. - M. Chung, Lee, Y., Lin, H. - H., and Wu, X., Constant-round Blind Classical Verification of Quantum Sampling, 2020.
Y. - H. Chen, Chung, K. - M., Lai, C. - Y., Vadhan, S. P., and Wu, X., Computational Notions of Quantum Min-Entropy, 2017.
Y. Peng, Ying, M., and Wu, X., Algebraic Reasoning of Quantum Programs via Non-Idempotent Kleene Algebra, 2021.
Conference Paper
K. Hietala, Li, L., Gaur, A., Green, A., Rand, R., Wu, X., and Hicks, M., Expanding the VOQC Toolkit, in The Second International Workshop on Programming Languages for Quantum Computing (PLanQC 2021), 2021.