Learning compact and efficient feature representations
Zhuo Su (Ph.D. Student)
Energy efficient sensing and computing is vital at all levels, from the smallest sensor like the chip to ultra high performance processors and systems like the cloud, especially in the post Moore's Law era. Energy efficient AI enables AI to move beyond the cloud and to reach the edge, which is critical to the progress of advancing AI and making AI ubiquitous over the next decade. Developing efficient, yet hardware-friendly algorithms such as deep network compression and efficient neural architecture search is essential to enable energy efficient AI.
|Primary Host:||Li Liu (University of Oulu)|
|Exchange Host:||Max Welling (University of Amsterdam)|
|PhD Duration:||01 October 2018 - 31 December 2022|
|Exchange Duration:||01 March 2021 - 31 August 2021|