Luo Mai
Luo Mai
Assistant Professor, The University of Edinburgh
Verified email at - Homepage
Cited by
Cited by
TensorLayer: A Versatile Library for Efficient Deep Learning Development
H Dong, A Supratak, L Mai, F Liu, A Oehmichen, S Yu, Y Guo
ACM Multimedia (Open Source Software Competition), 2017
NetAgg: Using Middleboxes for Application-specific On-path Aggregation in Data Centres
L Mai, L Rupprecht, A Alim, P Costa, M Migliavacca, P Pietzuch, AL Wolf
10th ACM Conference on emerging Networking EXperiments and Technologies …, 2014
Optimizing Network Performance in Distributed Machine Learning
L Mai, C Hong, P Costa
7th USENIX Workshop on Hot Topics in Cloud Computing (HotCloud'15), 2015
Chi: A Scalable and Programmable Control Plane for Distributed Stream Processing Systems
L Mai, K Zeng, R Potharaju, L Xu, S Suh, S Venkataraman, P Costa, T Kim, ...
VLDB, 2018
Emu: Rapid Prototyping of Networking Services
N Sultana, S Galea, D Greaves, M Wojcik, J Shipton, R Clegg, L Mai, ...
CrossBow: Scaling Deep Learning with Small Batch Sizes on Multi-GPU Servers
A Koliousis, P Watcharapichat, M Weidlich, L Mai, P Costa, P Pietzuch
VLDB, 2019
Load Balanced Rendezvous Data Collection in Wireless Sensor Networks
L Mai, L Shangguan, C Lang, J Du, H Liu, Z Li
8th IEEE Conference on Mobile Adhoc and Sensor Systems (MASS'11), 282-291, 2011
KungFu: Making Training in Distributed Machine Learning Adaptive
L Mai, G Li, M Wagenländer, K Fertakis, AO Brabete, P Pietzuch
USENIX OSDI, 937-954, 2020
Rendezvous Data Collection Using a Mobile Element in Heterogeneous Sensor Networks
J Du, H Liu, L Shangguan, L Mai, K Wang, S Li
International Journal of Distributed Sensor Networks 2012, 2012
FLICK: Developing and Running Application-specific Network Services
A Alim, RG Clegg, L Mai, L Rupprecht, E Seckler, P Costa, P Pietzuch, ...
USENIX ATC, 1-14, 2016
Exploiting Time-malleability in Cloud-based Batch Processing Systems
L Mai, E Kalyvianaki, P Costa
7th Workshop on Large-Scale Distributed Systems and Middleware (LADIS'13), 2013
Energy-efficient Heterogeneous Data Collection in Mobile Wireless Sensor Networks
L Shangguan, L Mai, J Du, W He, H Liu
Proceedings of the PMECT of IEEE ICCCN, 2011
Move Fast and Meet Deadlines: Fine-grained Real-time Stream Processing with Cameo
L Xu, S Venkataraman, I Gupta, L Mai, R Potharaju
Spotnik: Designing Distributed Machine Learning for Transient Cloud Resources
M Wagenländer, L Mai, G Li, P Pietzuch
USENIX HotCloud, 2020
Taming Hyper-parameters in Deep Learning Systems
L Mai, A Koliousis, G Li, AO Brabete, P Pietzuch
ACM SIGOPS Operating Systems Review 53 (1), 52-58, 2019
Supporting application-specific in-network processing in data centres
L Mai, L Rupprecht, P Costa, M Migliavacca, P Pietzuch, AL Wolf
Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM, 519-520, 2013
Towards a Network Marketplace in a Cloud
D Yu, L Mai, S Arianfar, R Fonseca, O Krieger, D Oran
8th USENIX Workshop on Hot Topics in Cloud Computing (HotCloud 16), 2016
Fast and Flexible Human Pose Estimation with HyperPose
Y Guo, J Liu, G Li, L Mai, H Dong
ACM Multimedia (Open Source Software Competition), 2021
Extending programs with debug-related features, with application to hardware development
N Sultana, S Galea, D Greaves, M Wójcik, N Zilberman, R Clegg, L Mai, ...
arXiv preprint arXiv:1705.09902, 2017
Efficient Reinforcement Learning Development with RLzoo
Z Ding, T Yu, Y Huang, H Zhang, G Li, Q Guo, L Mai, H Dong
ACM Multimedia (Open Source Software Competition), 2021
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