재정 지원 요구사항을 통해 공개된 자료 - Jian Li자세히 알아보기
제공된 곳이 없음: 1
DRL-D: Revenue-aware online service function chain deployment via deep reinforcement learning
Q Fan, P Pan, X Li, S Wang, J Li, J Wen
IEEE Transactions on Network and Service Management 19 (4), 4531-4545, 2022
재정 지원 요구사항 정책: National Natural Science Foundation of China
제공된 곳이 있음: 39
Online Algorithms for Multi-shop Ski Rental with Machine Learned Advice
S Wang, J Li, S Wang
Advances in Neural Information Processing Systems 33, 2020
재정 지원 요구사항 정책: US Department of Defense
Seizing Critical Learning Periods in Federated Learning
G Yan, H Wang, J Li
Proceedings of the AAAI Conference on Artificial Intelligence 36 (8), 8788-8796, 2022
재정 지원 요구사항 정책: US National Science Foundation, US Department of Energy
PA-cache: Evolving learning-based popularity-aware content caching in edge networks
Q Fan, X Li, J Li, Q He, K Wang, J Wen
IEEE Transactions on Network and Service Management 18 (2), 1746-1757, 2021
재정 지원 요구사항 정책: National Natural Science Foundation of China
DR-cache: Distributed resilient caching with latency guarantees
J Li, TK Phan, WK Chai, D Tuncer, G Pavlou, D Griffin, M Rio
IEEE INFOCOM 2018-IEEE Conference on Computer Communications, 441-449, 2018
재정 지원 요구사항 정책: US Department of Defense, European Commission
Accelerating serverless computing by harvesting idle resources
H Yu, H Wang, J Li, X Yuan, SJ Park
Proceedings of the ACM Web Conference 2022, 1741-1751, 2022
재정 지원 요구사항 정책: US National Science Foundation
Online Peak-Aware Energy Scheduling with Untrusted Advice
R Lee, J Maghakian, M Hajiesmaili, J Li, R Sitaraman, Z Liu
Proc. of ACM e-Energy, 2021
재정 지원 요구사항 정책: US National Science Foundation, US Department of Energy
Accurate learning or fast mixing? Dynamic adaptability of caching algorithms
J Li, S Shakkottai, JCS Lui, V Subramanian
IEEE Journal on Selected Areas in Communications 36 (6), 1314-1330, 2018
재정 지원 요구사항 정책: US National Science Foundation
gl2vec: Learning feature representation using graphlets for directed networks
K Tu, J Li, D Towsley, D Braines, LD Turner
Proceedings of the 2019 IEEE/ACM international conference on advances in …, 2019
재정 지원 요구사항 정책: US Department of Defense
Quickest detection of dynamic events in networks
S Zou, VV Veeravalli, J Li, D Towsley
IEEE Transactions on Information Theory, 2019
재정 지원 요구사항 정책: US National Science Foundation, US Department of Defense
Reinforcement Learning Augmented Asymptotically Optimal Index Policy for Finite-Horizon Restless Bandits
G Xiong, J Li, R Singh
Proceedings of the AAAI Conference on Artificial Intelligence 36 (8), 8726-8734, 2022
재정 지원 요구사항 정책: US National Science Foundation, US Department of Energy
Criticalfl: A critical learning periods augmented client selection framework for efficient federated learning
G Yan, H Wang, X Yuan, J Li
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023
재정 지원 요구사항 정책: US National Science Foundation, US Department of Defense
A TTL-based Approach for Data Aggregation in Geo-distributed Streaming Analytics
D Kumar, J Li, A Chandra, R Sitaraman
Proceedings of the ACM on Measurement and Analysis of Computing Systems (ACM …, 2019
재정 지원 요구사항 정책: US National Science Foundation, US Department of Defense
Network Cache Design under Stationary Requests: Exact Analysis and Poisson Approximation
NK Panigrahy, J Li, D Towsley, CV Hollot
Computer Networks, 107379, 2020
재정 지원 요구사항 정책: US National Science Foundation, US Department of Defense
Hit Rate vs. Hit Probability Based Cache Utility Maximization
NK Panigrahy, J Li, D Towsley
ACM MAMA, 2017
재정 지원 요구사항 정책: US National Science Foundation
Defl: Defending against model poisoning attacks in federated learning via critical learning periods awareness
G Yan, H Wang, X Yuan, J Li
Proceedings of the AAAI Conference on Artificial Intelligence 37 (9), 10711 …, 2023
재정 지원 요구사항 정책: US National Science Foundation, US Department of Energy
A ttl-based approach for content placement in edge networks
NK Panigrahy, J Li, F Zafari, D Towsley, P Yu
EAI International Conference on Performance Evaluation Methodologies and …, 2021
재정 지원 요구사항 정책: US National Science Foundation, US Department of Energy
Reinforcement learning for dynamic dimensioning of cloud caches: A restless bandit approach
G Xiong, S Wang, G Yan, J Li
IEEE/ACM Transactions on Networking 31 (5), 2147-2161, 2023
재정 지원 요구사항 정책: US National Science Foundation, US Department of Energy
Index-aware reinforcement learning for adaptive video streaming at the wireless edge
G Xiong, X Qin, B Li, R Singh, J Li
Proceedings of the Twenty-Third International Symposium on Theory …, 2022
재정 지원 요구사항 정책: US National Science Foundation, US Department of Energy, Department of …
Mean field games in nudge systems for societal networks
J Li, B Xia, X Geng, H Ming, S Shakkottai, V Subramanian, L Xie
ACM Transactions on Modeling and Performance Evaluation of Computing Systems …, 2018
재정 지원 요구사항 정책: US National Science Foundation
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