OpML

Publications

2020

2020 USENIX Conference on Operational Machine Learning, OpML 2020, July 28 - August 7, 2020. OpML (2020)
Alexandru A. Ormenisan, Moritz Meister, Fabio Buso, Robin Andersson, Seif Haridi, Jim Dowling
Time Travel and Provenance for Machine Learning Pipelines. OpML (2020)
Jiawen Liu, Zhen Xie, Dimitrios S. Nikolopoulos, Dong Li
RIANN: Real-time Incremental Learning with Approximate Nearest Neighbor on Mobile Devices. OpML (2020)
Thomas Rausch, Waldemar Hummer, Vinod Muthusamy
An Experimentation and Analytics Framework for Large-Scale AI Operations Platforms. OpML (2020)
Lisa Veiber, Kevin Allix, Yusuf Arslan, Tegawendé F. Bissyandé, Jacques Klein
Challenges Towards Production-Ready Explainable Machine Learning. OpML (2020)
Fabio Casati, Veeru Metha, Gopal Sarda, Sagar Davasam, Kannan Govindarajan
Detecting Feature Eligibility Illusions in Enterprise AI Autopilots. OpML (2020)
Edward Verenich, Alvaro Velasquez, M. G. Sarwar Murshed, Faraz Hussain
FlexServe: Deployment of PyTorch Models as Flexible REST Endpoints. OpML (2020)
Abdul Dakkak, Cheng Li, Jinjun Xiong, Wen-mei W. Hwu
DLSpec: A Deep Learning Task Exchange Specification. OpML (2020)
Chandra Mohan Meena, Sarwesh Suman, Vijay Agneeswaran
Finding Bottleneck in Machine Learning Model Life Cycle. OpML (2020)
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. OpML (2020)
Shunya Ueta, Suganprabu Nagaraja, Mizuki Sango
Auto Content Moderation in C2C e-Commerce. OpML (2020)

2019