Hong, Lichan

10 publications

ICLRW 2024 Conditional Transformer Fine-Tuning by Adaptive Layer Skipping Xingjian Zhang, Jiaxi Tang, Yang Liu, Xinyang Yi, Li Wei, Lichan Hong, Qiaozhu Mei, Ed H. Chi

ICML 2024 LEVI: Generalizable Fine-Tuning via Layer-Wise Ensemble of Different Views Yuji Roh, Qingyun Liu, Huan Gui, Zhe Yuan, Yujin Tang, Steven Euijong Whang, Liang Liu, Shuchao Bi, Lichan Hong, Ed H. Chi, Zhe Zhao

NeurIPS 2023 Recommender Systems with Generative Retrieval Shashank Rajput, Nikhil Mehta, Anima Singh, Raghunandan Hulikal Keshavan, Trung Vu, Lukasz Heldt, Lichan Hong, Yi Tay, Vinh Tran, Jonah Samost, Maciej Kula, Ed Chi, Maheswaran Sathiamoorthy

NeurIPS 2023 Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems Benjamin Coleman, Wang-Cheng Kang, Matthew Fahrbach, Ruoxi Wang, Lichan Hong, Ed Chi, Derek Cheng

NeurIPS 2022 Improving Multi-Task Generalization via Regularizing Spurious Correlation Ziniu Hu, Zhe Zhao, Xinyang Yi, Tiansheng Yao, Lichan Hong, Yizhou Sun, Ed Chi

AISTATS 2021 Learning-to-Rank with Partitioned Preference: Fast Estimation for the Plackett-Luce Model Jiaqi Ma, Xinyang Yi, Weijing Tang, Zhe Zhao, Lichan Hong, Ed Chi, Qiaozhu Mei

NeurIPS 2021 DSelect-K: Differentiable Selection in the Mixture of Experts with Applications to Multi-Task Learning Hussein Hazimeh, Zhe Zhao, Aakanksha Chowdhery, Maheswaran Sathiamoorthy, Yihua Chen, Rahul Mazumder, Lichan Hong, Ed Chi

ICLR 2019 Efficient Training on Very Large Corpora via Gramian Estimation Walid Krichene, Nicolas Mayoraz, Steffen Rendle, Li Zhang, Xinyang Yi, Lichan Hong, Ed Chi, John Anderson

ICMLW 2019 Improving Relevance Prediction with Transfer Learning in Large-Scale Retrieval Systems Ruoxi Wang, Zhe Zhao, Xinyang Yi, Ji Yang, Derek Zhiyuan Cheng, Lichan Hong, Steve Tjoa, Jieqi Kang, Evan Ettinger, Ed Chi

AAAI 2019 SNR: Sub-Network Routing for Flexible Parameter Sharing in Multi-Task Learning Jiaqi Ma, Zhe Zhao, Jilin Chen, Ang Li, Lichan Hong, Ed H. Chi