Suivre
Pijika Watcharapichat
Pijika Watcharapichat
BenevolentAI
Adresse e-mail validée de benevolent.ai
Titre
Citée par
Citée par
Année
Ako: Decentralised deep learning with partial gradient exchange
P Watcharapichat, VL Morales, RC Fernandez, P Pietzuch
Proceedings of the Seventh ACM Symposium on Cloud Computing, 84-97, 2016
792016
CROSSBOW: scaling deep learning with small batch sizes on multi-gpu servers
A Koliousis, P Watcharapichat, M Weidlich, L Mai, P Costa, P Pietzuch
arXiv preprint arXiv:1901.02244, 2019
382019
Meta-dataflows: Efficient exploratory dataflow jobs
R Castro Fernandez, W Culhane, P Watcharapichat, M Weidlich, ...
Proceedings of the 2018 International Conference on Management of Data, 1157 …, 2018
62018
Image processing and classification algorithm to detect cancerous cells morphology when using in-vivo probe-based confocal laser endomicroscopy for the lower gastrointestinal tract
P Watcharapichat
Department of Computing. Imperial College 65, 2012
32012
Browserflow: Imprecise data flow tracking to prevent accidental data disclosure
I Papagiannis, P Watcharapichat, D Muthukumaran, P Pietzuch
Proceedings of the 17th International Middleware Conference, 1-13, 2016
22016
Browserflow: Imprecise data flow tracking to prevent accidental data disclosure
I Papagiannis, P Watcharapichat, D Muthukumaran, P Pietzuch
Proceedings of the 17th International Middleware Conference, 1-13, 2016
22016
Synonymy in the Language of Colour
D Mylonas, A Koliousis, M Uusküla, I Chelombiev, D Justus, D Orr, ...
Proceedings of the 14th International Colour Association Conference (AIC'21 …, 2021
2021
Improving the performance of dataflow systems for deep neural network training
P Watcharapichat
Imperial College London, 2017
2017
Ako: Decentralised Deep Learning with Partial Gradient Exchange
P Pietzuch, P Watcharapichat, V Lopez Morales, R Castro Fernandez
ACM, 0
CrossBow: Scaling Deep Learning on Multi-GPU Servers
A Koliousis, P Watcharapichat, M Weidlich, P Costa, P Pietzuch
Le système ne peut pas réaliser cette opération maintenant. Veuillez réessayer plus tard.
Articles 1–10