Learning to Retrieve for Job Matching

no code implementations • 21 Feb 2024 • Jianqiang Shen, Yuchin Juan, Shaobo Zhang, Ping Liu, Wen Pu, Sriram Vasudevan, Qingquan Song, Fedor Borisyuk, Kay Qianqi Shen, Haichao Wei, Yunxiang Ren, Yeou S. Chiou, Sicong Kuang, Yuan Yin, Ben Zheng, Muchen Wu, Shaghayegh Gharghabi, Xiaoqing Wang, Huichao Xue, Qi Guo, Daniel Hewlett, Luke Simon, Liangjie Hong, Wenjing Zhang

Web-scale search systems typically tackle the scalability challenge with a two-step paradigm: retrieval and ranking.

Recommendation Systems Retrieval

LiFT: A Scalable Framework for Measuring Fairness in ML Applications

no code implementations • 14 Aug 2020 • Sriram Vasudevan, Krishnaram Kenthapadi

Many internet applications are powered by machine learned models, which are usually trained on labeled datasets obtained through either implicit / explicit user feedback signals or human judgments.

Fairness