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TF-Ranking.pdf

1812.00073.pdf
Preview of TF-Ranking
🔗 Source: arxiv.org
📊 Size: 1.23 MB
👤 Author: Rama Kumar Pasumarthi, Sebastian Bruch, Xuanhui Wang, Cheng Li, Michael Bendersky, Marc Najork, Jan
⬇️ Downloads: 106

Summary

TF-Ranking is a scalable TensorFlow library for learning-to-rank, introduced by Google, which provides a highly configurable and easy-to-use API for solving large-scale ranking problems in deep learning, supporting different scoring mechanisms, loss functions, and evaluation metrics, and has been deployed in production systems within Google, demonstrating effectiveness in learning ranking functions for large-scale search and recommendation applications.

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Description

TF-Ranking is a scalable TensorFlow library for learning-to-rank, introduced by Google, which provides a highly configurable and easy-to-use API for solving...

Technical Information

  • File Format: PDF
  • File Size: 1.23 MB
  • Pages: 9
  • Language: EN
  • Author: Rama Kumar Pasumarthi, Sebastian Bruch, Xuanhui Wang, Cheng Li, Michael Bendersky, Marc Najork, Jan
  • Total Downloads: 106
  • Last Updated: 6 days ago

Document Overview

This PDF document about TF-Ranking provides comprehensive information and guidance. Whether you're a beginner or advanced user, this resource offers valuable insights into TF-Ranking.

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If you're interested in TF-Ranking, you might also want to explore:

TF-Ranking guideTF-Ranking tutorial

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