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Infrastructure for Usable Machine Learning: The Stanford DAWN Project
22 May 2017
Peter Bailis
K. Olukotun
Christopher Ré
Matei A. Zaharia
AI4TS
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Papers citing
"Infrastructure for Usable Machine Learning: The Stanford DAWN Project"
8 / 8 papers shown
Reasonable Scale Machine Learning with Open-Source Metaflow
Jacopo Tagliabue
Hugo Bowne-Anderson
Ville Tuulos
Savin Goyal
R. Cledat
David Berg
AIFin
AI4CE
237
7
0
21 Mar 2023
Software Engineering for AI-Based Systems: A Survey
ACM Transactions on Software Engineering and Methodology (TOSEM), 2021
Luís Cruz
Justus Bogner
Xavier Franch
Marc Oriol
Julien Siebert
Adam Trendowicz
Anna Maria Vollmer
Stefan Wagner
341
298
0
05 May 2021
OmniFair: A Declarative System for Model-Agnostic Group Fairness in Machine Learning
Hantian Zhang
Xu Chu
Abolfazl Asudeh
S. Navathe
FaML
VLM
231
49
0
13 Mar 2021
Democratisation of Usable Machine Learning in Computer Vision
R. Bond
A. Koene
A. Dix
J. Boger
M. Mulvenna
M. Galushka
Brendon Bradley
Fiona Browne
Hui Wang
A. Wong
154
6
0
18 Feb 2019
Deep Reinforcement Learning
Yuxi Li
VLM
OffRL
433
139
0
15 Oct 2018
PANDA: Facilitating Usable AI Development
Jinyang Gao
Wei Wang
Meihui Zhang
Gang Chen
H. V. Jagadish
Guoliang Li
Teck Khim Ng
Beng Chin Ooi
Sheng Wang
Jingren Zhou
274
4
0
26 Apr 2018
Ease.ml: Towards Multi-tenant Resource Sharing for Machine Learning Workloads
Tian Li
Jie Zhong
Ji Liu
Wentao Wu
Ce Zhang
119
76
0
24 Aug 2017
Deep Reinforcement Learning: An Overview
Yuxi Li
OffRL
VLM
1.2K
1,798
0
25 Jan 2017
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