modeling Articles

  • Render Models at LinkedIn

    November 22, 2022

    Co-Authors: Mahesh Vishwanath, Eric Babyak, Sonali Bhadra, Umair Saeed Introduction We use render models for passing data to our client applications to describe the content (text, images, buttons etc.) and the layout to display on the screen. This means most of such logic is moved out of the clients and centralized on the server. This enables us to deliver new...

  • Ads CTR Graphic

    Challenges and practical lessons from building a deep-learning-based ads CTR prediction model

    August 29, 2022

    Co-authors: Ruoyan Wang, Sirou Zhu, Chengming Jiang Introduction At LinkedIn, our ads business is powered by click-through-rate (CTR) prediction, a core machine learning model. CTR prediction estimates the probability of clicks between a LinkedIn member and a potential advertisement. That probability is then used for ads auctions, which decide the order of ads...

  • graph-of-fast-tree-shap-version-comparison

    FastTreeSHAP: Accelerating SHAP value computation for trees

    March 15, 2022

    Co-authors: Jilei Yang, Humberto Gonzalez, Parvez Ahammad In this blog post, we introduce and announce the open sourcing of the FastTreeSHAP package, a Python package based on the paper Fast TreeSHAP: Accelerating SHAP Value Computation for Trees (presented at the NeurIPS2021 XAI4Debugging Workshop). FastTreeSHAP enables an efficient interpretation of tree-based...

  • Total Traffic Rate

    Taming Database Replication Latency by Capacity Planning

    May 19, 2014

    Web companies like LinkedIn handle a large amount of incoming traffic. Events generated in response to user input or actions are...