Fully Quantizing a Simplified Transformer for End-to-end Speech Recognition. - Alex Bie; Bharat Venkitesh; Joao Monteiro; Md. Akmal Haidar; Mehdi Rezagholizadeh (CoRR, 2019)

Don't Generate Me: Training Differentially Private Generative Models with Sinkhorn Divergence. - Tianshi Cao; Alex Bie; Arash Vahdat; Sanja Fidler; Karsten Kreis (NeurIPS, 2021)

Private Estimation with Public Data. - Alex Bie; Gautam Kamath 001; Vikrant Singhal (NeurIPS, 2022)

Distribution Learnability and Robustness. - Shai Ben-David; Alex Bie; Gautam Kamath 001; Tosca Lechner (NeurIPS, 2023)

Private Distribution Learning with Public Data: The View from Sample Compression. - Shai Ben-David; Alex Bie; Clément L. Canonne; Gautam Kamath 001; Vikrant Singhal (NeurIPS, 2023)

Normalization Is All You Need: Understanding Layer-Normalized Federated Learning under Extreme Label Shift. - Guojun Zhang; Mahdi Beitollahi; Alex Bie; Xi Chen 009 (CoRR, 2023)

Private GANs, Revisited. - Alex Bie; Gautam Kamath 001; Guojun Zhang (Trans. Mach. Learn. Res., 2023)

Private prediction for large-scale synthetic text generation. - Kareem Amin 002; Alex Bie; Weiwei Kong; Alexey Kurakin; Natalia Ponomareva 001; Umar Syed; Andreas Terzis; Sergei Vassilvitskii (EMNLP (Findings), 2024)

Parametric Feature Transfer: One-shot Federated Learning with Foundation Models. - Mahdi Beitollahi; Alex Bie; Sobhan Hemati; Leo Maxime Brunswic; Xu Li 001; Xi Chen 009; Guojun Zhang (CoRR, 2024)

Understanding the Role of Layer Normalization in Label-Skewed Federated Learning. - Guojun Zhang; Mahdi Beitollahi; Alex Bie; Xi Chen 009 (Trans. Mach. Learn. Res., 2024)

Foundation Models Meet Federated Learning: A One-shot Feature-sharing Method with Privacy and Performance Guarantees. - Mahdi Beitollahi; Alex Bie; Sobhan Hemati; Leo Maxime Brunswic; Xu Li 001; Xi Chen 009; Guojun Zhang (Trans. Mach. Learn. Res., 2025)

Escaping Collapse: The Strength of Weak Data for Large Language Model Training. - Kareem Amin 002; Sara Babakniya; Alex Bie; Weiwei Kong; Umar Syed; Sergei Vassilvitskii (CoRR, 2025)

Clustering and Median Aggregation Improve Differentially Private Inference. - Kareem Amin 002; Salman Avestimehr; Sara Babakniya; Alex Bie; Weiwei Kong; Natalia Ponomareva 001; Umar Syed (CoRR, 2025)