Production Machine Learning Pipelines: Empirical Analysis and Optimization Opportunities

30 March 2021

Papers citing "Production Machine Learning Pipelines: Empirical Analysis and Optimization Opportunities"

7 / 7 papers shown

Title
Data Makes Better Data Scientists Jinjin Zhao A. Gal Sanjay Krishnan 57 2 0 27 May 2024
Approximate Nearest Neighbour Search on Dynamic Datasets: An Investigation Ben Harwood Amir Dezfouli Iadine Chadès Conrad Sanderson 61 0 0 30 Apr 2024
The Pipeline for the Continuous Development of Artificial Intelligence Models -- Current State of Research and Practice M. Steidl Michael Felderer Rudolf Ramler 59 48 0 21 Jan 2023
Operationalizing Machine Learning: An Interview Study Shreya Shankar Rolando Garcia J. M. Hellerstein Aditya G. Parameswaran 116 54 0 16 Sep 2022
Machine Learning Featurizations for AI Hacking of Political Systems Nathan Sanders B. Schneier 56 2 0 08 Oct 2021
Understanding Data Storage and Ingestion for Large-Scale Deep Recommendation Model Training Mark Zhao Niket Agarwal Aarti Basant B. Gedik Satadru Pan ... Kevin Wilfong Harsha Rastogi Carole-Jean Wu Christos Kozyrakis Parikshit Pol GNN 84 76 0 20 Aug 2021
Preventing Machine Learning Poisoning Attacks Using Authentication and Provenance Jack W. Stokes P. England K. Kane AAML 62 15 0 20 May 2021