人才队伍
李彤阳
李彤阳 助理教授

+86 (0)10 6276-6141

tongyangli

静园五院103-1

量子算法设计(特别是量子机器学习、量子优化算法)、量子复杂性理论、量子模拟、量子游走 https://www.tongyangli.com

简介

  李彤阳博士,现任北京大学前沿计算研究中心助理教授,博士生导师,北京大学博雅青年学者,于2021年7月正式加入中心。他于2015年在清华大学交叉信息研究院(姚班)和数学科学系分别获得工学士学位和理学士学位,2020年在美国马里兰大学获得博士学位,之后在麻省理工学院从事博士后研究工作。他的科研围绕理论计算机、量子计算、人工智能的交叉领域展开,研究成果已在STOC、IEEE Transactions on Information Theory、ICML、NeurIPS、AAAI等发表论文十余篇;5次受邀在国际量子信息方向的权威会议 QIP上作报告;担任量子科学领域期刊Quantum的期刊编辑,以及相关领域多家顶级期刊和会议的审稿人,并于ICML 2020会议中荣获优秀审稿人奖(Top Reviewer Award)。曾获得IBM博士奖学金、美国自然科学基金委QISE-NET Triplet奖学金、以及马里兰大学Lanczos奖学金。

发表论著

■ (by contribution) Chenyi Zhang and Tongyang Li, Escape saddle points by a simple gradient-descent based algorithm, to appear in the 35th Annual Conference on Neural Information Processing Systems (NeurIPS 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. To appear in the 48th International Colloquium on Automata, Languages, and Programming (ICALP 2021). arXiv:2102.11349
■ Troy Lee, Tongyang Li, Miklos Santha, and Shengyu Zhang, On the cut dimension of a graph. To appear in the 2021 Computational Complexity Conference (CCC 2021). arXiv:2011.05085
■ (by contribution) Tongyang Li∗, Chunhao Wang∗, Shouvanik Chakrabarti, and Xiaodi Wu, Sublinear classical and quantum algorithms for general matrix games. To appear in the 35th AAAI Conference on Artificial Intelligence (AAAI 2021). arXiv:2012.06519
■ (by contribution) Daochen Wang∗, Xuchen You∗, Tongyang Li, and Andrew M. Childs, Quantum exploration algorithms for multi-armed bandits. To appear in the 35th AAAI Conference on Artificial Intelligence (AAAI 2021); also a contributed talk at the 4th Annual Conference on Quantum Techniques in Machine Learning (QTML 2020). arXiv:2007.07049
■ 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. arXiv:1901.03254
■ 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). arXiv:1910.06151
■ 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. arXiv:1902.00814
■ (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. arXiv:1911.00111
■ (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. arXiv:1904.02276
■ 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). arXiv:1809.01731
Tongyang Li and Xiaodi Wu, Quantum query complexity of entropy estimation. IEEE Transactions on Information Theory Vol. 65, no. 5, 2899–2921, 2019. arXiv:1710.06025
■ 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). arXiv:1710.02581
■ Andrew M. Childs and Tongyang Li, Efficient simulation of sparse Markovian quantum dynamics. Quantum Information & Computation 17 (2017), no. 11-12, 901–947,arXiv:1611.05543
■ (by contribution) Tongyang Li, Lei Song, Yongcai Wang, and Haisheng Tan, On Target Counting by Sequential Snapshots of Binary Proximity Sensors. In Proceedings of the 12th European Conference on Wireless Sensor Networks (EWSN 2015), pp. 19-34.

实验室

  量子算法实验室由李彤阳博士于2021年创立。该实验室专注于研究量子计算机上的算法,主要探讨机器学习、优化、统计学、数论、图论等方向的量子算法及其相对于经典计算的量子加速;也包括近期 NISQ (Noisy, Intermediate-Scale Quantum Computers) 量子计算机上的量子算法。更多信息可前往:https://cfcs.pku.edu.cn/research/research_labs/240405.htm