no code implementations • 27 Sep 2020 • Olga Poppe, Tayo Amuneke, Dalitso Banda, Aritra De, Ari Green, Manon Knoertzer, Ehi Nosakhare, Karthik Rajendran, Deepak Shankargouda, Meina Wang, Alan Au, Carlo Curino, Qun Guo, Alekh Jindal, Ajay Kalhan, Morgan Oslake, Sonia Parchani, Vijay Ramani, Raj Sellappan, Saikat Sen, Sheetal Shrotri, Soundararajan Srinivasan, Ping Xia, Shize Xu, Alicia Yang, Yiwen Zhu
Microsoft Azure is dedicated to guarantee high quality of service to its customers, in particular, during periods of high customer activity, while controlling cost.
no code implementations • WS 2020 • Liqun Shao, Sahitya Mantravadi, Tom Manzini, Alejandro Buendia, Manon Knoertzer, Soundar Srinivasan, Chris Quirk
In this paper, we detail novel strategies for interpolating personalized language models and methods to handle out-of-vocabulary (OOV) tokens to improve personalized language models.
1 code implementation • 20 Oct 2018 • Mark Hamilton, Sudarshan Raghunathan, Ilya Matiach, Andrew Schonhoffer, Anand Raman, Eli Barzilay, Karthik Rajendran, Dalitso Banda, Casey Jisoo Hong, Manon Knoertzer, Ben Brodsky, Minsoo Thigpen, Janhavi Suresh Mahajan, Courtney Cochrane, Abhiram Eswaran, Ari Green
We introduce Microsoft Machine Learning for Apache Spark (MMLSpark), an ecosystem of enhancements that expand the Apache Spark distributed computing library to tackle problems in Deep Learning, Micro-Service Orchestration, Gradient Boosting, Model Interpretability, and other areas of modern computation.