EdgeViTs: Competing Light-Weight CNNs on Mobile Devices with Vision Transformers. | 0 | 0.34 | 2022 |
NAS-Bench-ASR: Reproducible Neural Architecture Search for Speech Recognition | 0 | 0.34 | 2021 |
Smart at what cost?: characterising mobile deep neural networks in the wild | 0 | 0.34 | 2021 |
Zero-Cost Proxies for Lightweight NAS | 0 | 0.34 | 2021 |
BRP-NAS - Prediction-based NAS using GCNs. | 0 | 0.34 | 2020 |
Codesign-NAS - Automatic FPGA/CNN Codesign Using Neural Architecture Search. | 0 | 0.34 | 2020 |
Iterative Compression of End-to-End ASR Model using AutoML | 0 | 0.34 | 2020 |
Best Of Both Worlds: Automl Codesign Of A Cnn And Its Hardware Accelerator | 0 | 0.34 | 2020 |
Poster: MobiSR - Efficient On-Device Super-Resolution through Heterogeneous Mobile Processors. | 0 | 0.34 | 2019 |
ShrinkML: End-to-End ASR Model Compression Using Reinforcement Learning | 3 | 0.42 | 2019 |
MobiSR: Efficient On-Device Super-Resolution through Heterogeneous Mobile Processors | 8 | 0.48 | 2019 |
Dynamic Channel Pruning: Feature Boosting and Suppression. | 6 | 0.43 | 2018 |