Department of Industrial Engineering and Operations Research
University of California, Berkeley
Email: yingjiebi at berkeley dot edu
I received my B.S. in Microelectronics from Peking University in 2014 and my Ph.D. in Electrical and Computer Engineering from Cornell University in 2020. My research interests include nonconvex optimization, machine learning, computer networks and control theory. Here is a link to my CV.
- Y. Bi and J. Lavaei, “On the absence of spurious local minima in nonlinear low-rank matrix recovery problems,” preprint.
- Y. Ding, Y. Bi, and J. Lavaei, “Analysis of spurious local solutions of optimal control problems: One-shot optimization versus dynamic programming,” preprint.
- Y. Bi and J. Lavaei, “On the connectivity properties of feasible regions of optimal decentralized control problems,” preprint.
- Y. Bi and J. Lavaei, “Identifying the connectivity of feasible regions for optimal decentralized control problems,” to appear in IEEE CDC 2020.
- Y. Bi and A. Tang, “Duality gap estimation via a refined Shapley-Folkman lemma,” SIAM Journal on Optimization, vol. 30, no. 2, pp. 1094-1118, 2020.
- Y. Bi and A. Tang, “On upper bounding Shannon capacity of graph through generalized conic programming,” Optimization Letters, vol. 13, no. 6, pp. 1313-1323, Sep. 2019.
- Y. Bi and A. Tang, “Uncertainty-aware optimization for network provisioning and routing,” IEEE CISS 2019 (slides).
- N. Wu, Y. Bi, N. Michael, A. Tang, J. C. Doyle, and N. Matni, “A control-theoretic approach to in-network congestion management,” IEEE/ACM Transactions on Networking, vol. 26, no. 6, pp. 2443-2456, Dec. 2018.
- Y. Bi and D. Lynch, “A dynamic-programming-based cost analysis of 100G, 200G, and 400G transmission rates,” preprint.
- Y. Bi and A. Tang, “Cost of not arbitrarily splitting in routing,” IEEE ICNP 2017 (slides).
- N. Wu, Y. Bi, N. Michael, A. Tang, J. Doyle, and N. Matni, “HFTraC: High-frequency traffic control,” ACM SIGMETRICS 2017.
- Y. Bi, C. W. Tan, and A. Tang, “Network utility maximization with path cardinality constraints,” IEEE INFOCOM 2016 (slides).
- B. Gao, Y. Bi et al., “Ultra-low-energy three-dimensional oxide-based electronic synapses for implementation of robust high-accuracy neuromorphic computation systems,” ACS Nano, vol. 8, no. 7, pp. 6998-7004, Jul. 2014.