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Journal Articles
- 2020
[j1]Ahmed T. Elthakeb, Prannoy Pilligundla, Fatemehsadat Mireshghallah, Amir Yazdanbakhsh
, Hadi Esmaeilzadeh:
ReLeQ : A Reinforcement Learning Approach for Automatic Deep Quantization of Neural Networks. IEEE Micro 40(5): 37-45 (2020)
Conference and Workshop Papers
- 2020
- [c2]Byung Hoon Ahn, Prannoy Pilligundla, Amir Yazdanbakhsh, Hadi Esmaeilzadeh:
Chameleon: Adaptive Code Optimization for Expedited Deep Neural Network Compilation. ICLR 2020 - [c1]Ahmed Taha Elthakeb, Prannoy Pilligundla, Fatemeh Mireshghallah, Alexander Cloninger, Hadi Esmaeilzadeh:
Divide and Conquer: Leveraging Intermediate Feature Representations for Quantized Training of Neural Networks. ICML 2020: 2880-2891
Informal and Other Publications
- 2020
- [i6]Byung Hoon Ahn, Prannoy Pilligundla, Amir Yazdanbakhsh, Hadi Esmaeilzadeh:
Chameleon: Adaptive Code Optimization for Expedited Deep Neural Network Compilation. CoRR abs/2001.08743 (2020) - [i5]Ahmed T. Elthakeb, Prannoy Pilligundla, Fatemehsadat Mireshghallah, Tarek Elgindi, Charles-Alban Deledalle, Hadi Esmaeilzadeh:
Gradient-Based Deep Quantization of Neural Networks through Sinusoidal Adaptive Regularization. CoRR abs/2003.00146 (2020) - 2019
- [i4]Ahmed T. Elthakeb, Prannoy Pilligundla, Hadi Esmaeilzadeh:
SinReQ: Generalized Sinusoidal Regularization for Automatic Low-Bitwidth Deep Quantized Training. CoRR abs/1905.01416 (2019) - [i3]Byung Hoon Ahn, Prannoy Pilligundla, Hadi Esmaeilzadeh:
Reinforcement Learning and Adaptive Sampling for Optimized DNN Compilation. CoRR abs/1905.12799 (2019) - [i2]Ahmed T. Elthakeb, Prannoy Pilligundla, Hadi Esmaeilzadeh:
Divide and Conquer: Leveraging Intermediate Feature Representations for Quantized Training of Neural Networks. CoRR abs/1906.06033 (2019) - 2018
- [i1]Ahmed T. Elthakeb, Prannoy Pilligundla, Amir Yazdanbakhsh, Sean Kinzer, Hadi Esmaeilzadeh:
ReLeQ: A Reinforcement Learning Approach for Deep Quantization of Neural Networks. CoRR abs/1811.01704 (2018)
Coauthor Index
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