Charbel Sakr - RankMe

36 papers A* 3A 3B 1C 1Misc 3Journal 20Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	BCQ: Block Clustered Quantization for 4-bit (W4A4) LLM Inference. CoRR Reena Elangovan, Charbel Sakr, Anand Raghunathan, Brucek Khailany
2025	J	`jnl`	FGMP: Fine-Grained Mixed-Precision Weight and Activation Quantization for Hardware-Accelerated LLM Inference. CoRR Coleman Hooper, Charbel Sakr, Ben Keller, Rangharajan Venkatesan, Kurt Keutzer, Yakun Sophia Shao, Brucek Khailany
2025	J	`jnl`	LO-BCQ: Locally Optimal Block Clustered Quantization for 4-bit (W4A4) LLM Inference. Trans. Mach. Learn. Res. Reena Elangovan, Charbel Sakr, Anand Raghunathan, Brucek Khailany
2025	J	`jnl`	ThinKV: Thought-Adaptive KV Cache Compression for Efficient Reasoning Models. CoRR Akshat Ramachandran, Marina Neseem, Charbel Sakr, Rangharajan Venkatesan, Brucek Khailany, Tushar Krishna
2024	A*	`conf`	ESPACE: Dimensionality Reduction of Activations for Model Compression. NeurIPS Charbel Sakr, Brucek Khailany
2024	J	`jnl`	ESPACE: Dimensionality Reduction of Activations for Model Compression. CoRR Charbel Sakr, Brucek Khailany
2024	J	`jnl`	EoRA: Training-free Compensation for Compressed LLM with Eigenspace Low-Rank Approximation. CoRR Shih-Yang Liu, Huck Yang, Chein-Yi Wang, Nai Chit Fung, Hongxu Yin, Charbel Sakr, Saurav Muralidharan, Kwang-Ting Cheng, Jan Kautz, Yu-Chiang Frank Wang, Pavlo Molchanov, Min-Hung Chen
2023	J	`jnl`	A 95.6-TOPS/W Deep Learning Inference Accelerator With Per-Vector Scaled 4-bit Quantization in 5 nm. IEEE J. Solid State Circuits Ben Keller, Rangharajan Venkatesan, Steve Dai, Stephen G. Tell, Brian Zimmer, Charbel Sakr, William J. Dally, C. Thomas Gray, Brucek Khailany
2023	A	`conf`	VaPr: Variable-Precision Tensors to Accelerate Robot Motion Planning. IROS Yu-Shun Hsiao, Siva Kumar Sastry Hari, Balakumar Sundaralingam, Jason Yik, Thierry Tambe, Charbel Sakr, Stephen W. Keckler, Vijay Janapa Reddi
2023	J	`jnl`	VaPr: Variable-Precision Tensors to Accelerate Robot Motion Planning. CoRR Yu-Shun Hsiao, Siva Kumar Sastry Hari, Balakumar Sundaralingam, Jason Yik, Thierry Tambe, Charbel Sakr, Stephen W. Keckler, Vijay Janapa Reddi
2022	J	`jnl`	Fundamental Limits on Energy-Delay-Accuracy of In-Memory Architectures in Inference Applications. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Sujan K. Gonugondla, Charbel Sakr, Hassan Dbouk, Naresh R. Shanbhag
2022	A*	`conf`	Optimal Clipping and Magnitude-aware Differentiation for Improved Quantization-aware Training. ICML Charbel Sakr, Steve Dai, Rangharajan Venkatesan, Brian Zimmer, William J. Dally, Brucek Khailany
2022	J	`jnl`	Optimal Clipping and Magnitude-aware Differentiation for Improved Quantization-aware Training. CoRR Charbel Sakr, Steve Dai, Rangharajan Venkatesan, Brian Zimmer, William J. Dally, Brucek Khailany
2021	J	`jnl`	A 0.44-μJ/dec, 39.9-μs/dec, Recurrent Attention In-Memory Processor for Keyword Spotting. IEEE J. Solid State Circuits Hassan Dbouk, Sujan K. Gonugondla, Charbel Sakr, Naresh R. Shanbhag
2021	—	`—`	Finite precision deep learning with theoretical guarantees Charbel Sakr
2021	A	`conf`	Optimizing Selective Protection for CNN Resilience. ISSRE Abdulrahman Mahmoud, Siva Kumar Sastry Hari, Christopher W. Fletcher, Sarita V. Adve, Charbel Sakr, Naresh R. Shanbhag, Pavlo Molchanov, Michael B. Sullivan, Timothy Tsai, Stephen W. Keckler
2021	J	`jnl`	Signal Processing Methods to Enhance the Energy Efficiency of In-Memory Computing Architectures. IEEE Trans. Signal Process. Charbel Sakr, Naresh R. Shanbhag
2020	J	`jnl`	Fundamental Limits on Energy-Delay-Accuracy of In-memory Architectures in Inference Applications. CoRR Sujan Kumar Gonugondla, Charbel Sakr, Hassan Dbouk, Naresh R. Shanbhag
2020	A	`conf`	Fundamental Limits on the Precision of In-memory Architectures. ICCAD Sujan K. Gonugondla, Charbel Sakr, Hassan Dbouk, Naresh R. Shanbhag
2020	J	`jnl`	HarDNN: Feature Map Vulnerability Evaluation in CNNs. CoRR Abdulrahman Mahmoud, Siva Kumar Sastry Hari, Christopher W. Fletcher, Sarita V. Adve, Charbel Sakr, Naresh R. Shanbhag, Pavlo Molchanov, Michael B. Sullivan, Timothy Tsai, Stephen W. Keckler
2020	—	`conf`	KeyRAM: A 0.34 uJ/decision 18 k decisions/s Recurrent Attention In-memory Processor for Keyword Spotting. CICC Hassan Dbouk, Sujan K. Gonugondla, Charbel Sakr, Naresh R. Shanbhag
2019	—	`conf`	Accumulation Bit-Width Scaling For Ultra-Low Precision Training Of Deep Networks. ICLR (Poster) Charbel Sakr, Naigang Wang, Chia-Yu Chen, Jungwook Choi, Ankur Agrawal, Naresh R. Shanbhag, Kailash Gopalakrishnan
2019	J	`jnl`	Accumulation Bit-Width Scaling For Ultra-Low Precision Training Of Deep Networks. CoRR Charbel Sakr, Naigang Wang, Chia-Yu Chen, Jungwook Choi, Ankur Agrawal, Naresh R. Shanbhag, Kailash Gopalakrishnan
2019	J	`jnl`	Minimum Precision Requirements of General Margin Hyperplane Classifiers. IEEE J. Emerg. Sel. Topics Circuits Syst. Charbel Sakr, Yongjune Kim, Naresh R. Shanbhag
2019	—	`conf`	Per-Tensor Fixed-Point Quantization of the Back-Propagation Algorithm. ICLR (Poster) Charbel Sakr, Naresh R. Shanbhag
2018	Misc	`conf`	An Analytical Method to Determine Minimum Per-Layer Precision of Deep Neural Networks. ICASSP Charbel Sakr, Naresh R. Shanbhag
2018	—	`conf`	Minimum Precision Requirements for Deep Learning with Biomedical Datasets. BioCAS Charbel Sakr, Naresh R. Shanbhag
2018	J	`jnl`	Per-Tensor Fixed-Point Quantization of the Back-Propagation Algorithm. CoRR Charbel Sakr, Naresh R. Shanbhag
2018	Misc	`conf`	True Gradient-Based Training of Deep Binary Activated Neural Networks Via Continuous Binarization. ICASSP Charbel Sakr, Jungwook Choi, Zhuo Wang, Kailash Gopalakrishnan, Naresh R. Shanbhag
2017	A*	`conf`	Analytical Guarantees on Numerical Precision of Deep Neural Networks. ICML Charbel Sakr, Yongjune Kim, Naresh R. Shanbhag
2017	Misc	`conf`	Minimum precision requirements for the SVM-SGD learning algorithm. ICASSP Charbel Sakr, Ameya Patil, Sai Zhang, Yongjune Kim, Naresh R. Shanbhag
2017	C	`conf`	PredictiveNet: An energy-efficient convolutional neural network via zero prediction. ISCAS Yingyan Lin, Charbel Sakr, Yongjune Kim, Naresh R. Shanbhag
2016	J	`jnl`	Reducing the Energy Cost of Inference via In-sensor Information Processing. CoRR Sai Zhang, Mingu Kang, Charbel Sakr, Naresh R. Shanbhag
2016	J	`jnl`	Understanding the Energy and Precision Requirements for Online Learning. CoRR Charbel Sakr, Ameya Patil, Sai Zhang, Naresh R. Shanbhag
2000	J	`jnl`	Carrier-Sense Protocols for Packet-Switched Smart Antenna Basestations. Int. J. Wirel. Inf. Networks Charbel Sakr, Terence D. Todd
1997	B	`conf`	Carrier-sense protocols for packet-switched smart antenna basestations. ICNP Charbel Sakr, Terence D. Todd