modeling Articles

  • 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 stored in a source database. Though these events can be directly consumed by simply connecting to the source database where the events are first inserted, many of today's major web companies feature more complicated data flows, and so...