53 citations · 322 across the 16 of their papers we have counts for
17 papers
Towards an AI Software Factory for Data Systems
Anna Pavlenko, Bogdan Crivat, Brandon Haynes +23
AI-assisted coding tools deliver significant acceleration of coding, but only limited impact across the end-to-end software development lifecycle (SDLC)--an Amdahl's law effect! In…
A Tensor Compiler for Unified Machine Learning Prediction Serving
Supun Nakandala, Karla Saur, Gyeong-In Yu +4
Machine Learning (ML) adoption in the enterprise requires simpler and more efficient software infrastructure---the bespoke solutions typical in large web companies are simply unten…
MLOS: An Infrastructure for Automated Software Performance Engineering
Carlo Curino, Neha Godwal, Brian Kroth +9
Developing modern systems software is a complex task that combines business logic programming and Software Performance Engineering (SPE). The later is an experimental and labor-int…
Data Science through the looking glass and what we found there
Fotis Psallidas, Yiwen Zhu, Bojan Karlas +8
The recent success of machine learning (ML) has led to an explosive growth both in terms of new systems and algorithms built in industry and academia, and new applications built by…
FLAML: A Fast and Lightweight AutoML Library
Chi Wang, Qingyun Wu, Markus Weimer +1
We study the problem of using low computational cost to automate the choices of learners and hyperparameters for an ad-hoc training dataset and error metric, by conducting trials o…
Extending Relational Query Processing with ML Inference
Konstantinos Karanasos, Matteo Interlandi, Doris Xin +10
The broadening adoption of machine learning in the enterprise is increasing the pressure for strict governance and cost-effective performance, in particular for the common and cons…