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Prannoy Pilligundla
Prannoy Pilligundla
Master's in Computer Science at University of California, San Diego
在 eng.ucsd.edu 的电子邮件经过验证 - 首页
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ReLeQ : A Reinforcement Learning Approach for Automatic Deep Quantization of Neural Networks
AT Elthakeb, P Pilligundla, F Mireshghallah, A Yazdanbakhsh, ...
IEEE micro 40 (5), 37-45, 2020
131*2020
Chameleon: Adaptive code optimization for expedited deep neural network compilation
BH Ahn, P Pilligundla, A Yazdanbakhsh, H Esmaeilzadeh
International Conference on Learning Representations (ICLR), 2020
103*2020
Releq: an automatic reinforcement learning approach for deep quantization of neural networks
A Elthakeb, P Pilligundla, FS Mireshghallah, A Yazdanbakhsh, S Gao, ...
NeurIPS ML for Systems workshop, 2018, 2019
362019
Divide and conquer: Leveraging intermediate feature representations for quantized training of neural networks
AT Elthakeb, P Pilligundla, F Mireshghallah, A Cloninger, ...
International Conference on Machine Learning, 2880-2891, 2020
122020
SinReQ: Generalized sinusoidal regularization for automatic low-bitwidth deep quantized training
AT Elthakeb, P Pilligundla, H Esmaeilzadeh
arXiv preprint arXiv:1905.01416, 2019
82019
WaveQ: Gradient-based deep quantization of neural networks through sinusoidal adaptive regularization
AT Elthakeb, P Pilligundla, F Mireshghallah, T Elgindi, CA Deledalle, ...
arXiv preprint arXiv:2003.00146, 2020
72020
Gradient-based deep quantization of neural networks through sinusoidal adaptive regularization
AT Elthakeb, P Pilligundla, F Mireshghallah, T Elgindi, CA Deledalle, ...
arXiv preprint arXiv:2003.00146, 2020
62020
WAVEQ: GRADIENT-BASED DEEP QUANTIZATION OF NEURAL NETWORKS THROUGH SINUSOIDAL REGULARIZATION
AT Elthakeb, P Pilligundla, T Elgindi, F Mireshghallah, CA Deledalle, ...
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