Technical Program

08:00 Breakfast

08:45 Opening Remarks

09:00 - 10:00 Keynote

          

10:00 - 10:20 Break

10:20 - 11:00 Session 1

     
RSTensorFlow: GPU Enabled TensorFlow for Deep Learning on Commodity Android Devices
Moustafa Alzantot, Yingnan Wang, Zhengshuang Ren, Mani Srivastava (UCLA)

     
On-device Deep Reinforcement Learning for Embedded and Mobile Devices 
Rui Lowe (University College London), Sourav Bhattacharya (Nokia Bell Labs), David Nunes (University College London and University of Coimbra – Portugal), Akhil Mathur (Nokia Bell Labs), Nicholas Lane (University College London and Nokia Bell Labs)

11:00 - 12:00 Keynote

          

12:00 - 13:10 Lunch

13:10 - 13:50 Session 2

     
MobiRNN: Efficient Recurrent Neural Network Execution on Mobile GPU  
Qingqing Cao, Niranjan Balasubramanian, Aruna Balasubramanian (Stony Brook University)

     
Pruning Filters and Classes: Towards On-Device Customization of Convolutional Neural Networks  
Jia Guo, Miodrag Potkonjak (UCLA)

13:50 - 14:50 Keynote

          

14:50 - 15:10 Coffee

15:10 - 15:50 Session 3

     
Practical Processing of Mobile Sensor Data for Continual Deep Learning Predictions  
Kleomenis Katevas (Queen Mary University of London), Ilias Leontiadis, Martin Pielot, Joan Serra (Telefonica Research)

     
Design and Implementation of the Vehicular Camera System using Deep Neural Network Compression  
Beomjun Kim, Yongsu Jeon, Heejin Park, Dongheon Han, Yunju Baek (South Korea Pusan National University)

15:50 - 16:50 Panel

     
"The Road Ahead for Embedded and Mobile Deep Learning"

Pete Warden
(Google Brain)
Laurens van der Maaten
(Facebook AI Research)
Andreas Moshovos
(University of Toronto)

16:50 - 17:00 Closing Remarks