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OpML '19: 2019 USENIX Conference on Operational Machine Learning

10:30am PDT

Opportunities and Challenges Of Machine Learning Accelerators In Production Winchester RoomRajagopal Ananthanarayanan • Peter Brandt • Maheswaran Sathiamoorthy • Manasi Joshi

10:50am PDT

Accelerating Large Scale Deep Learning Inference through DeepCPU at Microsoft Winchester RoomMinjia Zhang • Samyam Rajbandari • Wenhan Wang • Elton Zheng • Olatunji Ruwase • Jeff Rasley • Jason Li • Junhua Wang • Yuxiong He

11:10am PDT

A Distributed Machine Learning For Giant Hogweed Eradication Winchester RoomMasaru Dobashi • Naoto Umemori

11:30am PDT

AIOps: Challenges and Experiences in Azure Winchester RoomZe Li • Yingnong Dang

11:50am PDT

Quasar: A High-Performance Scoring and Ranking Library Winchester RoomAndris Birkmanis • Fei Chen

12:10pm PDT

AI from Labs to Production - Challenges and Learnings Winchester RoomP Satya Madhuri • Malini Christina Raj • Ramprakash Ramamoorthy

1:30pm PDT

Deep Learning Lifecycle Management with Kubernetes, REST, and Python Winchester RoomBoris Tvaroska

2:30pm PDT

ModelOps on AWS Winchester RoomJohn Calhoun

4:00pm PDT

Accelerating the Machine Learning Lifecycle with MLflow Winchester RoomAndrew Chen

5:00pm PDT

Consistent Multi-Cloud AI Lifecycle Management with Kubeflow Winchester RoomDebo Dutta • Xinyuan Huang