no code implementations • 1 Mar 2024 • Ghazal Fazelnia, Sanket Gupta, Claire Keum, Mark Koh, Ian Anderson, Mounia Lalmas
In the second stage, downstream task-specific models leverage user representations via transfer learning instead of curating user features individually.
no code implementations • NeurIPS 2020 • Zhenwen Dai, Praveen Chandar, Ghazal Fazelnia, Ben Carterette, Mounia Lalmas-Roelleke
A challenge that machine learning practitioners in the industry face is the task of selecting the best model to deploy in production.
no code implementations • 8 Sep 2020 • Greg Benton, Ghazal Fazelnia, Alice Wang, Ben Carterette
Podcast recommendation is a growing area of research that presents new challenges and opportunities.
no code implementations • 23 Dec 2018 • Ghazal Fazelnia, Mark Ibrahim, Ceena Modarres, Kevin Wu, John Paisley
Models for sequential data such as the recurrent neural network (RNN) often implicitly model a sequence as having a fixed time interval between observations and do not account for group-level effects when multiple sequences are observed.
no code implementations • ICML 2018 • Ghazal Fazelnia, John Paisley
In this paper, we introduce a new approach to solving the variational inference optimization based on convex relaxation and semidefinite programming.