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ORCIDTIML@ISCA 2017: Toronto, ON, Canada
- Proceedings of the Workshop on Trends in Machine-Learning (and impact on computer architecture), TIML@ISCA 2017, Toronto, ON, Canada, June 25, 2017. ACM 2017, ISBN 978-1-4503-5564-3
- Karin Strauss, Olivier Temam:
Introduction to the workshop on trends in machine learning. 1 - Bill Dally:
Efficient methods and hardware for deep learning. 2 - Jason Mars:
Enhancing human capabilities. 3 - Ofer Dekel:
Machine learning on the edge. 4 - Yoshua Bengio:
Towards more hardware-friendly deep learning. 5 - Scott LeGrand:
All I want for Christmas... is a CUDA ASIC. 6 - Ali Farhadi:
Toward visual intelligence. 7 - Tianqi Chen:
An end to end IR stack for deep learning systems. 8 - Vincent Vanhoucke:
Learning to co-design. 9 - Carey K. Kloss:
Memory bandwidth in deep learning hardware. 10 - Yangqing Jia:
ML computation patterns in production systems. 11 - Eugenio Culurciello:
Snowflake: deep neural network accelerator. 12 - Gregory F. Diamos:
The road to exascale AI. 13
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