Google AI Open-Sources Rax: Composable Learning-to-Rank Using JAX | C2C Community

Google AI Open-Sources Rax: Composable Learning-to-Rank Using JAX

  • 23 August 2022
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Today, I’ll introuduce with Google cloud AI latest libray Rax, a library for LTR in the JAX ecosystem. Rax brings decades of LTR research to the JAX ecosystem, making it possible to apply JAX to a variety of ranking problems and combine ranking techniques with recent advances in deep learning built upon JAX (e.g., T5X). Rax provides state-of-the-art ranking losses, a number of standard ranking metrics, and a set of function transformations to enable ranking metric optimization. All this functionality is provided with a well-documented and easy to use API that will look and feel familiar to JAX users. Please check out our paper for more technical details.

 

Click on the below link to read more details.


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