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ORCID5th DEEM@SIGMOD 2021: Virtual Event, China
- Matthias Boehm, Julia Stoyanovich, Steven Whang:
Proceedings of the Fifth Workshop on Data Management for End-To-End Machine Learning, In conjunction with the 2021 ACM SIGMOD/PODS Conference, DEEM@SIGMOD 2021, Virtual Event, China, 20 June, 2021. ACM 2021, ISBN 978-1-4503-8486-5 - Wentao Wu, Ce Zhang:
Towards understanding end-to-end learning in the context of data: machine learning dancing over semirings & Codd's table. 1:1-1:4 - Nantia Makrynioti, Ruy Ley-Wild, Vasilis Vassalos:
Machine learning in SQL by translation to TensorFlow. 2:1-2:11 - Rui Liu, Sanjay Krishnan, Aaron J. Elmore
, Michael J. Franklin:
Understanding and optimizing packed neural network training for hyper-parameter tuning. 3:1-3:11 - Fatma Özcan, Chuan Lei, Abdul Quamar, Vasilis Efthymiou:
Semantic enrichment of data for AI applications. 4:1-4:7 - Hantian Zhang, Nima Shahbazi, Xu Chu, Abolfazl Asudeh:
FairRover: explorative model building for fair and responsible machine learning. 5:1-5:10 - Lena Wiese, Deborah Höltje:
NNCompare: a framework for dataset selection, data augmentation and comparison of different neural networks for medical image analysis. 6:1-6:7
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last updated on 2024-09-12 02:37 CEST by the dblp team
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