Jonathan Valverde

According to our database, Jonathan Valverde authored at least 4 papers between 2022 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Self-Auxiliary Distillation for Sample Efficient Learning in Google-Scale Recommenders.

Yin Zhang, Ruoxi Wang, Xiang Li, Tiansheng Yao, Andrew Evdokimov, Jonathan Valverde, Yuan Gao, Jerry Zhang, Evan Ettinger, Ed H. Chi, Derek Zhiyuan Cheng

Proceedings of the 18th ACM Conference on Recommender Systems, 2024

2023

Efficient Data Representation Learning in Google-scale Systems.

Derek Zhiyuan Cheng, Ruoxi Wang, Wang-Cheng Kang, Benjamin Coleman, Yin Zhang, Jianmo Ni, Jonathan Valverde, Lichan Hong, Ed H. Chi

Proceedings of the 17th ACM Conference on Recommender Systems, 2023

When Do Neural Nets Outperform Boosted Trees on Tabular Data?

Duncan C. McElfresh, Sujay Khandagale, Jonathan Valverde, Vishak Prasad C., Ganesh Ramakrishnan, Micah Goldblum, Colin White

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

On the Generalizability and Predictability of Recommender Systems.

Duncan C. McElfresh, Sujay Khandagale, Jonathan Valverde, John Dickerson, Colin White

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022