Luo Mai
Luo Mai
Assistant Professor at 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 (Best Open Source Software Award), 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
International Conference on emerging Networking EXperiments and Technologies …, 2014
Optimizing Network Performance in Distributed Machine Learning
L Mai, C Hong, P Costa
USENIX Workshop on Hot Topics in Cloud Computing (HotCloud), 2015
CrossBow: Scaling Deep Learning with Small Batch Sizes on Multi-GPU Servers
A Koliousis, P Watcharapichat, M Weidlich, L Mai, P Costa, P Pietzuch
International Conference on Very Large Data Bases (VLDB), 2019
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, ...
International Conference on Very Large Data Bases (VLDB), 2018
KungFu: Making Training in Distributed Machine Learning Adaptive
L Mai, G Li, M Wagenländer, K Fertakis, AO Brabete, P Pietzuch
USENIX Symposium on Operating Systems Design and Implementation (OSDI), 2020
Emu: Rapid Prototyping of Networking Services
N Sultana, S Galea, D Greaves, M Wojcik, J Shipton, R Clegg, L Mai, ...
USENIX Annual Technical Conference (ATC), 2017
Move Fast and Meet Deadlines: Fine-grained Real-time Stream Processing with Cameo
L Xu, S Venkataraman, I Gupta, L Mai, R Potharaju
USENIX Symposium on Networked Systems Design and Implementation (NSDI), 2021
Taming Hyper-parameters in Deep Learning Systems
L Mai, A Koliousis, G Li, AO Brabete, P Pietzuch
SIGOPS Operating Systems Review (Invited Paper), 2019
Ekko: A Large-Scale Deep Learning Recommender System with Low-Latency Model Update
C Sima, Y Fu, MK Sit, L Guo, X Gong, F Lin, J Wu, Y Li, H Rong, PL Aublin, ...
USENIX Symposium on Operating Systems Design and Implementation (OSDI), 2022
Load Balanced Rendezvous Data Collection in Wireless Sensor Networks
L Mai, L Shangguan, C Lang, J Du, H Liu, Z Li
IEEE MASS, 282-291, 2011
Spotnik: Designing Distributed Machine Learning for Transient Cloud Resources
M Wagenländer, L Mai, G Li, P Pietzuch
USENIX HotCloud, 2020
FLICK: Developing and Running Application-specific Network Services
A Alim, RG Clegg, L Mai, L Rupprecht, E Seckler, P Costa, P Pietzuch, ...
USENIX Annual Technical Conference (ATC), 2016
Rendezvous Data Collection Using a Mobile Element in Heterogeneous Sensor Networks
J Du, H Liu, L Shangguan, L Mai, K Wang, S Li
IJDSN, 2012
Fast and Flexible Human Pose Estimation with HyperPose
Y Guo, J Liu, G Li, L Mai, H Dong
ACM Multimedia, 2021
Large sequence models for sequential decision-making: a survey
M Wen, R Lin, H Wang, Y Yang, Y Wen, L Mai, J Wang, H Zhang, ...
Frontiers of Computer Science 17 (6), 176349, 2023
Exploiting Time-malleability in Cloud-based Batch Processing Systems
L Mai, E Kalyvianaki, P Costa
ACM LADIS (Co-located with SOSP), 2013
MegBA: A GPU-Based Distributed Library for Large-Scale Bundle Adjustment
J Ren, W Liang, R Yan, L Mai, S Liu, X Liu
European Conference on Computer Vision (ECCV), 2022
A Theoretical Understanding of Gradient Bias in Meta-Reinforcement Learning
B Liu, X Feng, J Ren, L Mai, R Zhu, H Zhang, J Wang, Y Yang
Conference on Neural Information Processing Systems (NeurIPS), 2022
Efficient Reinforcement Learning Development with RLzoo
Z Ding, T Yu, Y Huang, H Zhang, G Li, Q Guo, L Mai, H Dong
ACM Multimedia, 2021
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