Preprints

• (by contribution) Qi Zhao, You Zhou, Alexander F. Shaw, Tongyang Li, and Andrew M. Childs, Hamiltonian simulation with random inputs. In submission.

• Shouvanik Chakrabarti, Andrew M. Childs, Shih-Han Hung, Tongyang Li, Chunhao Wang, and Xiaodi Wu, Quantum algorithm for estimating volumes of convex bodies. In submission. Single-track contributed talk at the 23rd Annual Conference on Quantum Information Processing (QIP 2020; 17 among 283 submissions).

Publications

(Unless marked as "by contribution", the authors of papers are listed alphabetically. * marks equal contribution.)

• (by contribution) Chenyi Zhang and Tongyang Li, Escape saddle points by a simple gradient-descent based algorithm, to appear in the 35th Conference on Neural Information Processing Systems (NeurIPS 2021), 2021.

• (by contribution) Chenyi Zhang*, Jiaqi Leng*, and Tongyang Li, Quantum algorithms for escaping from saddle points. Quantum, 5:529, 2021.

• Andrew M. Childs, Shih-Han Hung, and Tongyang Li, Quantum query complexity with matrix-vector products. Proceedings of the 48th International Colloquium on Automata, Languages, and Programming (ICALP 2021), Vol. 198, 55:1-55:19, Leibniz International Proceedings in Informatics, 2021.

• Troy Lee, Tongyang Li, Miklos Santha, and Shengyu Zhang, On the cut dimension of a graph. Proceedings of the 36th Computational Complexity Conference (CCC 2021), Vol. 200, 15:1-15:35, Leibniz International Proceedings in Informatics, 2021.

• (by contribution) Tongyang Li∗, Chunhao Wang∗, Shouvanik Chakrabarti, and Xiaodi Wu, Sublinear classical and quantum algorithms for general matrix games. Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI 2021), 35(10): 8465-8473, 2021.

• (by contribution) Daochen Wang∗, Xuchen You∗, Tongyang Li, and Andrew M. Childs, Quantum exploration algorithms for multi-armed bandits. Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI 2021), 35(11): 10102-10110, 2021; also a contributed talk at the 4th Annual Conference on Quantum Techniques in Machine Learning (QTML 2020).

• Nai-Hui Chia, Tongyang Li, Han-Hsuan Lin, and Chunhao Wang, Quantum-inspired sublinear algorithm for solving low-rank semidefinite programming. Proceedings of the 45th International Symposium on Mathematical Foundations of Computer Science (MFCS 2020), Vol. 170, 23:1–23:15, Leibniz International Proceedings in Informatics, 2020.

• Nai-Hui Chia, András Gilyén, Tongyang Li, Han-Hsuan Lin, Ewin Tang, and Chunhao Wang, Sampling-based sublinear low-rank matrix arithmetic framework for dequantizing quantum machine learning. Proceedings of the 52nd Annual ACM Symposium on Theory of Computing (STOC 2020), 387–400, 2020; also a contributed talk at the 23rd Annual Conference on Quantum Information Processing (QIP 2020).

• András Gilyén and Tongyang Li, Distributional property testing in a quantum world. Proceedings of the 11th Annual Conference on Innovations in Theoretical Computer Science (ITCS 2020), Vol. 151, 25:1–25:19, Leibniz International Proceedings in Informatics, 2020.

• (by contribution) Shouvanik Chakrabarti*, Yiming Huang*, Tongyang Li, Soheil Feizi, and Xiaodi Wu, Quantum Wasserstein generative adversarial networks. Proceedings of the 33rd Annual Conference on Neural Information Processing Systems (NeurIPS 2019), 6778–6789, 2019.

• (by contribution) Tongyang Li, Shouvanik Chakrabarti, and Xiaodi Wu, Sublinear quantum algorithms for training linear and kernel-based classifiers. Proceedings of the 36th International Conference on Machine Learning (ICML 2019), 3815–3824, 2019.

• Shouvanik Chakrabarti, Andrew M. Childs, Tongyang Li, and Xiaodi Wu, Quantum algorithms and lower bounds for convex optimization, Quantum, 4:221, 2020; also a contributed talk at the 22nd Annual Conference on Quantum Information Processing (QIP 2019).

• Tongyang Li and Xiaodi Wu, Quantum query complexity of entropy estimation. IEEE Transactions on Information Theory Vol. 65, no. 5, 2899–2921, 2019.

• Fernando G.S.L. Brandão, Amir Kalev, Tongyang Li, Cedric Y.-Y. Lin, Krysta M. Svore, and Xiaodi Wu, Quantum SDP Solvers: Large Speed-ups, Optimality, and Applications to Quantum Learning. Proceedings of the 46th International Colloquium on Automata, Languages and Programming (ICALP 2019), Vol. 132, 27:1–27:14, Leibniz International Proceedings in Informatics, 2019; also a contributed talk at the 22nd Annual Conference on Quantum Information Processing (QIP 2019).

• Andrew M. Childs and Tongyang Li, Efficient simulation of sparse Markovian quantum dynamics. Quantum Information & Computation 17 (2017), no. 11-12, 901–947.