Iandola, Forrest

SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size

Iandola, F. N., Han, S., Moskewicz, M. W., Ashraf, K., Dally, W. J., & Keutzer, K. (2016) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 6,201

SqueezeDet: Unified, Small, Low Power Fully Convolutional Neural Networks for Real-Time Object Detection for Autonomous Driving

Wu, B., Wan, A., Iandola, F., Jin, P. H., & Keutzer, K. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Advanced Neural Network ApplicationsAutonomous Vehicle Technology and Safety

Cited by 614

SqueezeBERT: What can computer vision teach NLP about efficient neural networks?

Iandola, F., Shaw, A., Krishna, R., & Keutzer, K. (2020) · Proceedings of SustaiNLP: Workshop on Simple and Efficient Natural Language Processing

Advanced Neural Network ApplicationsTopic Modeling

Cited by 114

How to scale distributed deep learning?

Jin, P. H., Yuan, Q., Iandola, F., & Keutzer, K. (2016) · arXiv

Stochastic Gradient Optimization TechniquesDistributed Control Multi-Agent Systems

Cited by 85