OpML - researchr conference series publications

researchr

You are not signed in
Sign in
Sign up

Viewing Publication 1 - 28 from 28

2020

Challenges and Experiences with MLOps for Performance Diagnostics in Hybrid-Cloud Enterprise Software DeploymentsAmitabha Banerjee, Chien-Chia Chen, Chien-Chun Hung, Xiaobo Huang, Yifan Wang, Razvan Chevesaran. opml 2020: [doi]

Detecting Feature Eligibility Illusions in Enterprise AI AutopilotsFabio Casati, Veeru Metha, Gopal Sarda, Sagar Davasam, Kannan Govindarajan. opml 2020: [doi]

DLSpec: A Deep Learning Task Exchange SpecificationAbdul Dakkak, Cheng Li, Jinjun Xiong, Wen-mei W. Hwu. opml 2020: [doi]

RIANN: Real-time Incremental Learning with Approximate Nearest Neighbor on Mobile DevicesJiawen Liu, Zhen Xie, Dimitrios S. Nikolopoulos, Dong Li 0001. opml 2020: [doi]

Finding Bottleneck in Machine Learning Model Life CycleChandra Mohan Meena, Sarwesh Suman, Vijay Agneeswaran. opml 2020: [doi]

Time Travel and Provenance for Machine Learning PipelinesAlexandru A. Ormenisan, Moritz Meister, Fabio Buso, Robin Andersson, Seif Haridi, Jim Dowling. opml 2020: [doi]

An Experimentation and Analytics Framework for Large-Scale AI Operations PlatformsThomas Rausch, Waldermar Hummer, Vinod Muthusamy. opml 2020: [doi]

2020 USENIX Conference on Operational Machine Learning, OpML 2020, July 28 - August 7, 2020Nisha Talagala, Joel Young, editors, USENIX Association, 2020. [doi]

Auto Content Moderation in C2C e-CommerceShunya Ueta, Suganprabu Nagaraja, Mizuki Sango. opml 2020: [doi]

Challenges Towards Production-Ready Explainable Machine LearningLisa Veiber, Kevin Allix, Yusuf Arslan, Tegawendé F. Bissyandé, Jacques Klein. opml 2020: [doi]

FlexServe: Deployment of PyTorch Models as Flexible REST EndpointsEdward Verenich, Alvaro Velasquez, M. G. Sarwar Murshed, Faraz Hussain 0001. opml 2020: [doi]

2019

Opportunities and Challenges Of Machine Learning Accelerators In ProductionRajagopal Ananthanarayanan, Peter Brandt, Manasi Joshi, Maheswaran Sathiamoorthy. opml 2019: 1-3 [doi]

Shooting the moving target: machine learning in cybersecurityAnkit Arun, Ignacio Arnaldo. opml 2019: 13-14 [doi]

Continuous Training for Production ML in the TensorFlow Extended (TFX) PlatformDenis Baylor, Kevin Haas, Konstantinos Katsiapis, Sammy Leong, Rose Liu, Clemens Menwald, Hui Miao, Neoklis Polyzotis, Mitchell Trott, Martin Zinkevich. opml 2019: 51-53 [doi]

Stratum: A Serverless Framework for the Lifecycle Management of Machine Learning-based Data Analytics TasksAnirban Bhattacharjee, Yogesh D. Barve, Shweta Khare, Shunxing Bao, Aniruddha Gokhale, Thomas Damiano. opml 2019: 59-61 [doi]

KnowledgeNet: Disaggregated and Distributed Training and Serving of Deep Neural NetworksSaman Biookaghazadeh, Yitao Chen, Kaiqi Zhao, Ming Zhao 0002. opml 2019: 47-49 [doi]

Towards Taming the Resource and Data Heterogeneity in Federated LearningZheng Chai, Hannan Fayyaz, Zeshan Fayyaz, Ali Anwar, Yi Zhou, Nathalie Baracaldo, Heiko Ludwig, Yue Cheng. opml 2019: 19-21 [doi]

MPP: Model Performance PredictorSindhu Ghanta, Sriram Subramanian, Lior Khermosh, Harshil Shah, Yakov Goldberg, Swaminathan Sundararaman, Drew S. Roselli, Nisha Talagala. opml 2019: 23-25 [doi]

tensorflow-tracing: A Performance Tuning Framework for ProductionSayed Hadi Hashemi, Paul Rausch, Benjamin Rabe, Kuan-Yen Chou, Simeng Liu, Volodymyr V. Kindratenko, Roy H. Campbell. opml 2019: 31-33 [doi]

TonY: An Orchestrator for Distributed Machine Learning JobsAnthony Hsu, Keqiu Hu, Jonathan Hung, Arun Suresh, Zhe Zhang. opml 2019: 39-41 [doi]

Transfer Learning for Performance Modeling of Deep Neural Network SystemsMd Shahriar Iqbal, Lars Kotthoff, Pooyan Jamshidi. opml 2019: 43-46 [doi]

MLOp Lifecycle Scheme for Vision-based Inspection Process in ManufacturingJunsung Lim, Hoejoo Lee, Youngmin Won, Hunje Yeon. opml 2019: 9-11 [doi]

2019 USENIX Conference on Operational Machine Learning, OpML 2019, Santa Clara, CA, USA, May 20, 2019Bharath Ramsundar, Nisha Talagala, editors, USENIX Association, 2019. [doi]

Deep Learning Inference Service at MicrosoftJonathan Soifer, Jason Li, Mingqin Li, Jeffrey Zhu, Yingnan Li, Yuxiong He, Elton Zheng, Adi Oltean, Maya Mosyak, Chris Barnes, Thomas Liu, Junhua Wang. opml 2019: 15-17 [doi]

Low-latency Job Scheduling with Preemption for the Development of Deep LearningHidehito Yabuuchi, Daisuke Taniwaki, Shingo Omura. opml 2019: 27-30 [doi]

Disdat: Bundle Data Management for Machine Learning PipelinesKen Yocum, Sean Rowan, Jonathan Lunt, Theodore M. Wong. opml 2019: 35-37 [doi]

Accelerating Large Scale Deep Learning Inference through DeepCPU at MicrosoftMinjia Zhang, Samyam Rajbhandari, Wenhan Wang, Elton Zheng, Olatunji Ruwase, Jeff Rasley, Jason Li, Junhua Wang, Yuxiong He. opml 2019: 5-7 [doi]

Katib: A Distributed General AutoML Platform on KubernetesJinan Zhou, Andrey Velichkevich, Kirill Prosvirov, Anubhav Garg, Yuji Oshima, Debo Dutta. opml 2019: 55-57 [doi]

Sign in or sign up to see more results.

runs on WebDSL