Feb. 13, 2024, 5:41 a.m. | Fedor Borisyuk Mingzhou Zhou Qingquan Song Siyu Zhu Birjodh Tiwana Ganesh Parameswaran Siddharth Dangi

cs.LG updates on arXiv.org arxiv.org

We present LiRank, a large-scale ranking framework at LinkedIn that brings to production state-of-the-art modeling architectures and optimization methods. We unveil several modeling improvements, including Residual DCN, which adds attention and residual connections to the famous DCNv2 architecture. We share insights into combining and tuning SOTA architectures to create a unified model, including Dense Gating, Transformers and Residual DCN. We also propose novel techniques for calibration and describe how we productionalized deep learning based explore/exploit methods. To enable effective, production-grade …

architecture architectures art attention cs.ai cs.ir cs.lg framework improvements industrial insights linkedin modeling optimization production ranking residual scale sota state unified model

Research Scholar (Technical Research)

@ Centre for the Governance of AI | Hybrid; Oxford, UK

HPC Engineer (x/f/m) - DACH

@ Meshcapade GmbH | Remote, Germany

Director of Machine Learning

@ Axelera AI | Hybrid/Remote - Europe (incl. UK)

Senior Data Scientist - Trendyol Milla

@ Trendyol | Istanbul (All)

Data Scientist, Mid

@ Booz Allen Hamilton | USA, CA, San Diego (1615 Murray Canyon Rd)

Systems Development Engineer , Amazon Robotics Business Applications and Solutions Engineering

@ Amazon.com | Boston, Massachusetts, USA