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ORCIDOpML 2020
- Nisha Talagala, Joel Young:
2020 USENIX Conference on Operational Machine Learning, OpML 2020, July 28 - August 7, 2020. USENIX Association 2020
Session 1: Deep Learning and GPU Accelerated Data Science
- Abdul Dakkak, Cheng Li, Jinjun Xiong, Wen-mei W. Hwu:
DLSpec: A Deep Learning Task Exchange Specification.
Session 2: Model Life Cycle
- Chandra Mohan Meena, Sarwesh Suman, Vijay Agneeswaran:
Finding Bottleneck in Machine Learning Model Life Cycle.
Session 3: Features, Explainability, and Analytics
- Fabio Casati, Veeru Metha, Gopal Sarda, Sagar Davasam, Kannan Govindarajan:
Detecting Feature Eligibility Illusions in Enterprise AI Autopilots. - Alexandru A. Ormenisan, Moritz Meister, Fabio Buso, Robin Andersson, Seif Haridi, Jim Dowling:
Time Travel and Provenance for Machine Learning Pipelines. - Thomas Rausch, Waldemar Hummer, Vinod Muthusamy:
An Experimentation and Analytics Framework for Large-Scale AI Operations Platforms. - Lisa Veiber, Kevin Allix, Yusuf Arslan, Tegawendé F. Bissyandé, Jacques Klein:
Challenges Towards Production-Ready Explainable Machine Learning.
Session 4: Algorithms
- Jiawen Liu, Zhen Xie, Dimitrios S. Nikolopoulos, Dong Li:
RIANN: Real-time Incremental Learning with Approximate Nearest Neighbor on Mobile Devices.
Session 5: Model Deployment Strategies
- Edward Verenich
, Alvaro Velasquez, M. G. Sarwar Murshed, Faraz Hussain:
FlexServe: Deployment of PyTorch Models as Flexible REST Endpoints.
Session 6: Applications and Experiences
- Shunya Ueta, Suganprabu Nagaraja, Mizuki Sango:
Auto Content Moderation in C2C e-Commerce. - Amitabha Banerjee, Chien-Chia Chen, Chien-Chun Hung, Xiaobo Huang, Yifan Wang, Razvan Chevesaran:
Challenges and Experiences with MLOps for Performance Diagnostics in Hybrid-Cloud Enterprise Software Deployments.
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