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Ming Shi 0003
Person information
- affiliation: State University of New York at Buffalo, NY, USA
- affiliation (former): Ohio State University, Columbus, OH, USA
- affiliation (former): Purdue University, West Lafayette, IN, USA
Other persons with the same name
- Ming Shi — disambiguation page
- Ming Shi 0001 — Hubei University of Technology, Wuhan, Hubei, China
- Ming Shi 0002
— Fudan University, Shanghai, China - Ming Shi 0004
— Paul Scherrer Institute, Villigen, Switzerland
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2020 – today
- 2025
[j4]Ming Shi
, Xiaojun Lin
, Lei Jiao
:
Power-of-2-Arms for Adversarial Bandit Learning With Switching Costs. IEEE Trans. Netw. 33(3): 1112-1127 (2025)
[c9]Amirhossein Roknilamouki, Arnob Ghosh, Ming Shi, Fatemeh Nourzad, Eylem Ekici, Ness B. Shroff:
Provably Efficient RL for Linear MDPs under Instantaneous Safety Constraints in Non-Convex Feature Spaces. ICML 2025
[c8]Mohamed A. Abd-Elmagid
, Ming Shi
, Eylem Ekici
, Ness B. Shroff
:
Online Learning for Optimizing AoI-Energy Tradeoff under Unknown Channel Statistics. MobiHoc 2025: 271-280
[i6]Linfeng Cao, Ming Shi, Ness B. Shroff:
Provably Efficient Multi-Objective Bandit Algorithms under Preference-Centric Customization. CoRR abs/2502.13457 (2025)
[i5]Amirhossein Roknilamouki, Arnob Ghosh, Ming Shi, Fatemeh Nourzad, Eylem Ekici, Ness B. Shroff:
Provably Efficient RL for Linear MDPs under Instantaneous Safety Constraints in Non-Convex Feature Spaces. CoRR abs/2502.18655 (2025)
[i4]Mohamed A. Abd-Elmagid, Ming Shi, Eylem Ekici, Ness B. Shroff:
Online Learning for Optimizing AoI-Energy Tradeoff under Unknown Channel Statistics. CoRR abs/2509.18654 (2025)- 2024
[j3]Ming Shi
, Xiaojun Lin
, Lei Jiao
:
Combining Regularization With Look-Ahead for Competitive Online Convex Optimization. IEEE/ACM Trans. Netw. 32(3): 2391-2405 (2024)
[c7]Ming Shi, Yingbin Liang, Ness B. Shroff:
Designing Near-Optimal Partially Observable Reinforcement Learning. MILCOM 2024: 463-468- 2023
[c6]Ming Shi, Yingbin Liang, Ness B. Shroff:
Near-Optimal Adversarial Reinforcement Learning with Switching Costs. ICLR 2023
[c5]Ming Shi, Yingbin Liang, Ness B. Shroff:
A Near-Optimal Algorithm for Safe Reinforcement Learning Under Instantaneous Hard Constraints. ICML 2023: 31243-31268
[i3]Ming Shi, Yingbin Liang, Ness B. Shroff:
Near-Optimal Adversarial Reinforcement Learning with Switching Costs. CoRR abs/2302.04374 (2023)
[i2]Ming Shi, Yingbin Liang, Ness B. Shroff:
A Near-Optimal Algorithm for Safe Reinforcement Learning Under Instantaneous Hard Constraints. CoRR abs/2302.04375 (2023)
[i1]Ming Shi, Yingbin Liang, Ness B. Shroff:
Theoretical Hardness and Tractability of POMDPs in RL with Partial Hindsight State Information. CoRR abs/2306.08762 (2023)- 2022
[c4]Sen Lin, Ming Shi, Anish Arora, Raef Bassily, Elisa Bertino, Constantine Caramanis, Kaushik R. Chowdhury
, Eylem Ekici, Atilla Eryilmaz, Stratis Ioannidis
, Nan Jiang, Gauri Joshi, Jim Kurose, Yingbin Liang, Zhiqiang Lin, Jia Liu, Mingyan Liu, Tommaso Melodia
, Aryan Mokhtari, Rob Nowak, Sewoong Oh, Srini Parthasarathy, Chunyi Peng, Hulya Seferoglu, Ness B. Shroff, Sanjay Shakkottai, Kannan Srinivasan, Ameet Talwalkar, Aylin Yener, Lei Ying
:
Leveraging Synergies Between AI and Networking to Build Next Generation Edge Networks. CIC 2022: 16-25
[c3]Ming Shi, Xiaojun Lin, Lei Jiao
:
Power-of-2-arms for bandit learning with switching costs. MobiHoc 2022: 131-140- 2021
[j2]Ming Shi
, Xiaojun Lin
, Sonia Fahmy
:
Competitive Online Convex Optimization With Switching Costs and Ramp Constraints. IEEE/ACM Trans. Netw. 29(2): 876-889 (2021)
[c2]Ming Shi, Xiaojun Lin
, Lei Jiao
:
Combining Regularization with Look-Ahead for Competitive Online Convex Optimization. INFOCOM 2021: 1-10
2010 – 2019
- 2019
[j1]Ming Shi, Xiaojun Lin, Lei Jiao:
On the Value of Look-Ahead in Competitive Online Convex Optimization. Proc. ACM Meas. Anal. Comput. Syst. 3(2): 22:1-22:42 (2019)- 2018
[c1]Ming Shi, Xiaojun Lin, Sonia Fahmy
, Dong-Hoon Shin:
Competitive Online Convex Optimization with Switching Costs and Ramp Constraints. INFOCOM 2018: 1835-1843
Coauthor Index

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