Publications

Export 44 results:
Author Title [ Type(Asc)] Year
Filters: Author is Yi-Kai Liu  [Clear All Filters]
Journal Article
Y. - K. Liu, Universal low-rank matrix recovery from Pauli measurements, Advances in Neural Information Processing Systems (NIPS), pp. 1638-1646, 2011.
Y. - K. Liu, An Uncertainty Principle for the Curvelet Transform, and the Infeasibility of Quantum Algorithms for Finding Short Lattice Vectors, 2023.
Y. - K. Liu, An Uncertainty Principle for the Curvelet Transform, and the Infeasibility of Quantum Algorithms for Finding Short Lattice Vectors, 2023.
R. Perlner and Liu, Y. - K., Thermodynamic Analysis of Classical and Quantum Search Algorithms, 2017.
A. D. Bookatz, Jordan, S. P., Liu, Y. - K., and Wocjan, P., Testing quantum expanders is co-QMA-complete, Physical Review A, vol. 87, no. 4, 2013.
V. Dunjko, Liu, Y. - K., Wu, X., and Taylor, J. M., Super-polynomial and exponential improvements for quantum-enhanced reinforcement learning, 2017.
G. Alagic, Alperin-Sheriff, J., Apon, D., Cooper, D., Dang, Q., Kelsey, J., Liu, Y. - K., Miller, C., Moody, D., Peralta, R., Perlner, R., Robinson, A., and Smith-Tone, D., Status Report on the Second Round of the NIST Post-Quantum Cryptography Standardization Process, NISTIR 8309, 2020.
G. Alagic, Alperin-Sheriff, J., Apon, D., Cooper, D., Dang, Q., Miller, C., Moody, D., Peralta, R., Perlner, R., Robinson, A., Smith-Tone, D., and Liu, Y. - K., Status Report on the First Round of the NIST Post-Quantum Cryptography Standardization Process, School: National Institute for Standards and Technology , 2019.
A. Anandkumar, Foster, D. P., Hsu, D., Kakade, S. M., and Liu, Y. - K., A Spectral Algorithm for Latent Dirichlet Allocation, Algorithmica, pp. 193-214, 2012.
Y. - K. Liu, Single-shot security for one-time memories in the isolated qubits model, CRYPTO, vol. Part II, pp. 19-36, 2014.
I. Roth, Kueng, R., Kimmel, S., Liu, Y. - K., Gross, D., Eisert, J., and Kliesch, M., Recovering quantum gates from few average gate fidelities, Phys. Rev. Lett. , vol. 121, p. 170502, 2018.
K. Huang, Farfurnik, D., Seif, A., Hafezi, M., and Liu, Y. - K., Random Pulse Sequences for Qubit Noise Spectroscopy, 2023.
S. T. Flammia, Gross, D., Liu, Y. - K., and Eisert, J., Quantum Tomography via Compressed Sensing: Error Bounds, Sample Complexity, and Efficient Estimators , New Journal of Physics, vol. 14, no. 9, p. 095022, 2012.
D. Gross, Liu, Y. - K., Flammia, S. T., Becker, S., and Eisert, J., Quantum state tomography via compressed sensing, Physical Review Letters, vol. 105, no. 15, 2010.
A. Ambainis, Childs, A. M., and Liu, Y. - K., Quantum property testing for bounded-degree graphs, Proc. RANDOM, pp. 365-376, 2010.
S. P. Jordan and Liu, Y. - K., Quantum Cryptanalysis: Shor, Grover, and Beyond, IEEE Security & Privacy , vol. 16, no. 5, pp. 14-21, 2018.
S. Kimmel and Liu, Y. - K., Quantum Compressed Sensing Using 2-Designs, 2015.
Y. - K. Liu, Quantum Algorithms Using the Curvelet Transform, Proc. ACM Symposium on Theory of Computing (STOC), pp. 391-400, 2009.
Z. Ji, Liu, Y. - K., and Song, F., Pseudorandom States, Non-Cloning Theorems and Quantum Money, In: Shacham H., Boldyreva A. (eds) Advances in Cryptology – CRYPTO 2018. CRYPTO 2018. Lecture Notes in Computer Science., vol. 10993, 2018.
Y. - K. Liu, Privacy Amplification in the Isolated Qubits Model, Eurocrypt, pp. 785-814, 2014.
J. Rajakumar, Watson, J. D., and Liu, Y. - K., Polynomial-Time Classical Simulation of Noisy IQP Circuits with Constant Depth, 2024.
F. Krahmer and Liu, Y. - K., Phase Retrieval Without Small-Ball Probability Assumptions: Stability and Uniqueness, SampTA, pp. 411-414, 2015.
F. Krahmer and Liu, Y. - K., Phase Retrieval Without Small-Ball Probability Assumptions, IEEE Transactions on Information Theory , vol. 64, no. 1, pp. 485-500, 2018.
C. Shen, Heeres, R. W., Reinhold, P., Jiang, L., Liu, Y. - K., Schoelkopf, R. J., and Jiang, L., Optimized tomography of continuous variable systems using excitation counting, Physical Review A, vol. 94, p. 052327, 2016.
Y. - K. Liu, Christandl, M., and Verstraete, F., N-representability is QMA-complete, Phys. Rev. Lett., vol. 98, no. 11, 2007.