Publications

For a complete and most recent list of publications, please check out my Google Scholar page.

Journals

• Minimum Precision Requirements of General Margin Hyperplane Classifiers - Charbel Sakr, Yongjune Kim, Naresh Shanbhag - JETCAS 2019 - PDF.

Conferences

• KeyRAM: A 0.34 uJ/decision 18 k decisions/s Recurrent Attention In-memory Processor for Keyword Spotting - Hassan Dbouk, Sujan Gonugondla, Charbel Sakr, Naresh Shnabhag - CICC 2020 - (accepted)
• 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 - PDF - Poster.
• Per-Tensor Fixed-Point Quantization of the Back-Propagation Algorithm - Charbel Sakr, Naresh Shanbhag - ICLR 2019 - PDF - Poster.
• Minimum Precision Requirements for Deep Learning with Biomedical Datasets - Charbel Sakr, Naresh Shanbhag - BioCAS 2018 - PDF - Slides.
• An Analytical Method to Determine Minimum Per-layer Precision of Deep Neural Networks - Charbel Sakr, Naresh Shanbhag - ICASSP 2018 - PDF - Slides.
• True Gradient-based Training of Deep Binary Activated Neural Networks via Continuous Binarization - Charbel Sakr, Jungwook Choi, Zhuo Wang, Kailash Gopalakrishnan, Naresh Shanbhag - ICASSP 2018 - PDF - Slides.
• Analytical Guarantees on Numerical Precision of Deep Neural Networks - Charbel Sakr, Yongjune Kim, Naresh Shanbhag - ICML 2017 - PDF - Slides - Poster - Video.
• PredictiveNet: an Energy-Efficient Convolutional Neural Network via Zero Prediction - Yingyan Lin, Charbel Sakr, Yongjune Kim, Naresh Shanbhag - ISCAS 2017 - PDF - Poster.
• Minimum Precision Requirements for the SVM-SGD Learning Algorithm - Charbel Sakr, Ameya Patil, Sai Zhang, Yongjune Kim, Naresh Shanbhag - ICASSP 2017 - PDF - Slides.

Theses

• Master's Thesis: Analytical Guarantees for Reduced Precision Fixed-Point Margin Hyperplane Classifiers - Charbel Sakr - 2017 - PDF.

E-Prints

• Understanding the Energy the Energy and Precision Requirements for Online Learning - Charbel Sakr, Ameya Patil, Sai Zhang, Yongjune Kim, Naresh Shanbhag - arXiv.
• Reducing the Energy Cost of Inference via In-Sensor Information Processing - Sai Zhang, Mingu Kang, Charbel Sakr, Naresh Shanbhag - arXiv