mlsanityData to 7 Oct 2026

Scaling TensorFlow to 300 million predictions per second

arXiv 2109.09541 ↗First posted 20 Sep 2021cs.LG cs.PFcited by 2

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Abstract (arXiv)

We present the process of transitioning machine learning models to the TensorFlow framework at a large scale in an online advertising ecosystem. In this talk we address the key challenges we faced and describe how we successfully tackled them; notably, implementing the models in TF and serving them efficiently with low latency using various optimization techniques.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 3 of its 7 references that are in the map. First posted on arXiv 20 Sep 2021.

Builds on

3 of 7 references.

References · 3

  1. 2017DeepFM: A Factorization-Machine based Neural Network for CTR Predictioncited by 673
  2. 2016TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systemscited by 660
  3. 2016Display Advertising with Real-Time Bidding (RTB) and Behavioural Targetingcited by 42

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Citing papers per year: 2022: 1; 2023: 1.

2 papers.