Hou, Charlie

11 publications

TMLR 2025 Characterizing the Training Dynamics of Private Fine-Tuning with Langevin Diffusion Shuqi Ke, Charlie Hou, Sewoong Oh, Giulia Fanti

ICML 2025 Private Federated Learning Using Preference-Optimized Synthetic Data Charlie Hou, Mei-Yu Wang, Yige Zhu, Daniel Lazar, Giulia Fanti

ICLRW 2025 Private Federated Learning Using Preference-Optimized Synthetic Data Charlie Hou, Mei-Yu Wang, Yige Zhu, Daniel Lazar, Giulia Fanti

NeurIPSW 2024 Characterizing the Training Dynamics of Private Fine-Tuning with Langevin Diffusion Shuqi Ke, Charlie Hou, Sewoong Oh, Giulia Fanti

ICML 2024 PrE-Text: Training Language Models on Private Federated Data in the Age of LLMs Charlie Hou, Akshat Shrivastava, Hongyuan Zhan, Rylan Conway, Trang Le, Adithya Sagar, Giulia Fanti, Daniel Lazar

ICLRW 2024 PrE-Text: Training Language Models on Private Federated Data in the Age of LLMs Charlie Hou, Akshat Shrivastava, Hongyuan Zhan, Rylan Conway, Trang Le, Adithya Sagar, Giulia Fanti, Daniel Lazar

TMLR 2024 Pretrained Deep Models Outperform GBDTs in Learning-to-Rank Under Label Scarcity Charlie Hou, Kiran Koshy Thekumparampil, Michael Shavlovsky, Giulia Fanti, Yesh Dattatreya, Sujay Sanghavi

ICMLW 2024 Pretrained Deep Models Outperform GBDTs in Learning-to-Rank Under Label Scarcity Charlie Hou, Kiran Koshy Thekumparampil, Michael Shavlovsky, Giulia Fanti, Sujay Sanghavi

ICMLW 2023 Pretrained Deep Models Outperform GBDTs in Learning-to-Rank Under Label Scarcity Charlie Hou, Kiran Koshy Thekumparampil, Michael Shavlovsky, Giulia Fanti, Yesh Dattatreya, Sujay Sanghavi

ICLRW 2023 Privately Customizing Prefinetuning to Better Match User Data in Federated Learning Charlie Hou, Hongyuan Zhan, Akshat Shrivastava, Sid Wang, Aleksandr Livshits, Giulia Fanti, Daniel Lazar

ICLR 2022 FedChain: Chained Algorithms for Near-Optimal Communication Cost in Federated Learning Charlie Hou, Kiran Koshy Thekumparampil, Giulia Fanti, Sewoong Oh