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ORCIDDEEM@ACM SIGMOD Conference 2018: Houston, TX, USA
- Sebastian Schelter, Stephan Seufert, Arun Kumar:
Proceedings of the Second Workshop on Data Management for End-To-End Machine Learning, DEEM@SIGMOD 2018, Houston, TX, USA, June 15, 2018. ACM 2018 - Carsten Binnig, Benedetto Buratti, Yeounoh Chung, Cyrus Cousins, Tim Kraska, Zeyuan Shang, Eli Upfal, Robert C. Zeleznik, Emanuel Zgraggen:
Towards Interactive Curation & Automatic Tuning of ML Pipelines. 1:1-1:4 - Janani Balaji, Chris Min, Faizan Javed, Yun Zhu:
Avatar: Large Scale Entity Resolution of Heterogeneous User Profiles. 2:1-2:10 - Alexander Ratner, Braden Hancock, Jared Dunnmon, Roger E. Goldman, Christopher Ré:
Snorkel MeTaL: Weak Supervision for Multi-Task Learning. 3:1-3:4 - Jennifer Ortiz, Magdalena Balazinska, Johannes Gehrke, S. Sathiya Keerthi:
Learning State Representations for Query Optimization with Deep Reinforcement Learning. 4:1-4:4 - Nantia Makrynioti, Nikolaos Vasiloglou, Emir Pasalic, Vasilis Vassalos:
Modelling Machine Learning Algorithms on Relational Data with Datalog. 5:1-5:4 - Wail Y. Alkowaileet, Sattam Alsubaiee, Michael J. Carey, Chen Li, Heri Ramampiaro, Phanwadee Sinthong, Xikui Wang:
End-to-End Machine Learning with Apache AsterixDB. 6:1-6:10 - Jian Zhang, Max Lam, Stephanie Wang, Paroma Varma, Luigi Nardi, Kunle Olukotun
, Christopher Ré:
Exploring the Utility of Developer Exhaust. 7:1-7:7 - Mahmoud Abo Khamis, Hung Q. Ngo, XuanLong Nguyen, Dan Olteanu, Maximilian Schleich:
AC/DC: In-Database Learning Thunderstruck. 8:1-8:10 - Doris Xin, Litian Ma, Jialin Liu, Stephen Macke, Shuchen Song, Aditya G. Parameswaran:
Accelerating Human-in-the-loop Machine Learning: Challenges and Opportunities. 9:1-9:4 - Jose Picado, Arash Termehchy, Sudhanshu Pathak:
Learning Efficiently Over Heterogeneous Databases: Sampling and Constraints to the Rescue. 10:1-10:4
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