LiGNN: Graph Neural Networks at LinkedIn

no code implementations • 17 Feb 2024 • Fedor Borisyuk, Shihai He, Yunbo Ouyang, Morteza Ramezani, Peng Du, Xiaochen Hou, Chengming Jiang, Nitin Pasumarthy, Priya Bannur, Birjodh Tiwana, Ping Liu, Siddharth Dangi, Daqi Sun, Zhoutao Pei, Xiao Shi, Sirou Zhu, Qianqi Shen, Kuang-Hsuan Lee, David Stein, Baolei Li, Haichao Wei, Amol Ghoting, Souvik Ghosh

In this paper, we present LiGNN, a deployed large-scale Graph Neural Networks (GNNs) Framework.

Representation Learning

LiRank: Industrial Large Scale Ranking Models at LinkedIn

no code implementations • 10 Feb 2024 • Fedor Borisyuk, Mingzhou Zhou, Qingquan Song, Siyu Zhu, Birjodh Tiwana, Ganesh Parameswaran, Siddharth Dangi, Lars Hertel, Qiang Xiao, Xiaochen Hou, Yunbo Ouyang, Aman Gupta, Sheallika Singh, Dan Liu, Hailing Cheng, Lei Le, Jonathan Hung, Sathiya Keerthi, Ruoyan Wang, Fengyu Zhang, Mohit Kothari, Chen Zhu, Daqi Sun, Yun Dai, Xun Luan, Sirou Zhu, Zhiwei Wang, Neil Daftary, Qianqi Shen, Chengming Jiang, Haichao Wei, Maneesh Varshney, Amol Ghoting, Souvik Ghosh

We present LiRank, a large-scale ranking framework at LinkedIn that brings to production state-of-the-art modeling architectures and optimization methods.

Click-Through Rate Prediction Quantization

Measuring Long-term Impact of Ads on LinkedIn Feed

no code implementations • 29 Jan 2019 • Jinyun Yan, Birjodh Tiwana, Souvik Ghosh, Haishan Liu, Shaunak Chatterjee

In this paper, we design experiments to understand how members' behavior evolve over time given different ads experiences.

Adaptive Rate of Convergence of Thompson Sampling for Gaussian Process Optimization

no code implementations • 18 May 2017 • Kinjal Basu, Souvik Ghosh

We consider the problem of global optimization of a function over a continuous domain.

Thompson Sampling