Repository logo
Log in(current)
Repository logoMIT Open ScholarshipDSpace@MIT
  1. Home
  2. MIT Open Access Articles
  3. MIT Open Access Articles
  4. Practical Design of Performant Recommender Systems using Large-scale Linear Programming-based Global Inference

Practical Design of Performant Recommender Systems using Large-scale Linear Programming-based Global Inference

Thumbnail Image
Download
Name

3580305.3599183.pdf

Size

791.12 KB

Format

Adobe PDF

Checksum (MD5)

cce5674b8a9a5068468bc5d7065113af

Download all files submitted through automated deposit
3580305.3599183.zip (772.61 KB)
Author(s)
Gupta, Aman
•
Keerthi, S. Sathiya
•
Acharya, Ayan
•
Cheng, Miao
•
Ocejo Elizondo, Borja
•
Ramanath, Rohan
•
Mazumder, Rahul
•
Basu, Kinjal
•
Tay, J. Kenneth
•
Gupta, Rupesh
Date Issued
August 6, 2023
Publisher
ACM|Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
Citation
Gupta, Aman, Keerthi, S. Sathiya, Acharya, Ayan, Cheng, Miao, Ocejo Elizondo, Borja et al. 2023. "Practical Design of Performant Recommender Systems using Large-scale Linear Programming-based Global Inference."
Version
Final published version
MIT Department
Statistics and Data Science Center (Massachusetts Institute of Technology)
Sloan School of Management
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
https://hdl.handle.net/1721.1/152078
DOI of Published Version
https://doi.org/10.1145/3580305.3599183
Repository logo
PrivacyPermissionsAccessibilityContact us
Repository logo
Notify us about copyright concerns.