ReLeQ: A Reinforcement Learning Approach for Deep Quantization of Neural Networks. - Ahmed T. Elthakeb; Prannoy Pilligundla; Amir Yazdanbakhsh; Sean Kinzer; Hadi Esmaeilzadeh (CoRR, 2018)

SinReQ: Generalized Sinusoidal Regularization for Automatic Low-Bitwidth Deep Quantized Training. - Ahmed T. Elthakeb; Prannoy Pilligundla; Hadi Esmaeilzadeh (CoRR, 2019)

Reinforcement Learning and Adaptive Sampling for Optimized DNN Compilation. - Byung Hoon Ahn; Prannoy Pilligundla; Hadi Esmaeilzadeh (CoRR, 2019)

Divide and Conquer: Leveraging Intermediate Feature Representations for Quantized Training of Neural Networks. - Ahmed T. Elthakeb; Prannoy Pilligundla; Hadi Esmaeilzadeh (CoRR, 2019)

Chameleon: Adaptive Code Optimization for Expedited Deep Neural Network Compilation. - Byung Hoon Ahn; Prannoy Pilligundla; Amir Yazdanbakhsh; Hadi Esmaeilzadeh (ICLR, 2020)

Divide and Conquer: Leveraging Intermediate Feature Representations for Quantized Training of Neural Networks. - Ahmed Taha Elthakeb; Prannoy Pilligundla; Fatemeh Mireshghallah; Alexander Cloninger; Hadi Esmaeilzadeh (ICML, 2020)

Gradient-Based Deep Quantization of Neural Networks through Sinusoidal Adaptive Regularization. - Ahmed T. Elthakeb; Prannoy Pilligundla; Fatemehsadat Mireshghallah; Tarek Elgindi; Charles-Alban Deledalle; Hadi Esmaeilzadeh (CoRR, 2020)

ReLeQ : A Reinforcement Learning Approach for Automatic Deep Quantization of Neural Networks. - Ahmed T. Elthakeb; Prannoy Pilligundla; Fatemehsadat Mireshghallah; Amir Yazdanbakhsh; Hadi Esmaeilzadeh (IEEE Micro, 2020)