| 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 | 118* | 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 | 94* | 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 | 38 | 2019 |
| 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 | 10 | 2020 |
| SinReQ: Generalized sinusoidal regularization for automatic low-bitwidth deep quantized training AT Elthakeb, P Pilligundla, H Esmaeilzadeh arXiv preprint arXiv:1905.01416, 2019 | 8 | 2019 |
| 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 | 7 | 2020 |
| 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 | 6 | 2020 |
| WAVEQ: GRADIENT-BASED DEEP QUANTIZATION OF NEURAL NETWORKS THROUGH SINUSOIDAL REGULARIZATION AT Elthakeb, P Pilligundla, T Elgindi, F Mireshghallah, CA Deledalle, ... | | 2020 |
Hadi EsmaeilzadehAssociate Professor; Computer Science and Engineering; University of California, San DiegoVerified email at eng.ucsd.edu
