Sakr, Charbel

6 publications

TMLR 2025 LO-BCQ: Locally Optimal Block Clustered Quantization for 4-Bit (W4A4) LLM Inference Reena Elangovan, Charbel Sakr, Anand Raghunathan, Brucek Khailany

NeurIPS 2024 ESPACE: Dimensionality Reduction of Activations for Model Compression Charbel Sakr, Brucek Khailany

ICML 2022 Optimal Clipping and Magnitude-Aware Differentiation for Improved Quantization-Aware Training Charbel Sakr, Steve Dai, Rangha Venkatesan, Brian Zimmer, William Dally, Brucek Khailany

ICLR 2019 Accumulation Bit-Width Scaling for Ultra-Low Precision Training of Deep Networks Charbel Sakr, Naigang Wang, Chia-Yu Chen, Jungwook Choi, Ankur Agrawal, Naresh Shanbhag, Kailash Gopalakrishnan

ICLR 2019 Per-Tensor Fixed-Point Quantization of the Back-Propagation Algorithm Charbel Sakr, Naresh Shanbhag

ICML 2017 Analytical Guarantees on Numerical Precision of Deep Neural Networks Charbel Sakr, Yongjune Kim, Naresh Shanbhag