08:05 AM Qualcomm presentation on ML-optimized mobile hardware, Harris Teague

08:30 AM fpgaConvNet: A Toolflow for Mapping Diverse Convolutional Neural Networks on Embedded FPGAs, Stylianos Venieris

08:45 AM High performance ultra-low-precision convolutions on mobile devices, Andrew Tulloch, Yangqing Jia

09:00 AM Caffe2: Lessons from Running Deep Learning on the World’s Smart Phones, Yangqing Jia

09:30 AM CoreML: High-Performance On-Device Inference, Gaurav Kapoor

10:00 AM Data center to the edge: a journey with TensorFlow, Rajat Monga

10:30 AM Coffee Break

11:00 AM Panel: On-Device ML Frameworks, Jeff Gehlhaar, Yangqing Jia, Rajat Monga

11:45 AM Poster Spotlight 1 (list coming soon)

12:05 PM Lunch / Poster session 1

01:30 PM Federated learning for model training on decentralized data, Daniel Ramage

02:00 PM Personalized and Private Peer-to-Peer Machine Learning, Aurélien Bellet, Rachid Guerraoui, Marc Tommasi

02:15 PM SquishedNets: Squishing SqueezeNet further for edge device scenarios via deep evolutionary synthesis, Francis Li

02:30 PM A Cascade Architecture for Keyword Spotting on Mobile Devices, Raziel Alvarez, Chris Thornton, Mohammadali Ghodrat

02:45 PM Multiple-Instance, Cascaded Classification for Keyword Spotting in Narrow-Band Audio, Ahmad Abdulkader, Kareem Nassar, Mohamed Mahmoud, Daniel Galvez

03:00 PM Coffee Break

03:30 PM Alexa: On-device Natural Language Understanding, Arindam Mandal

04:00 PM Continuous low-power music recognition, TBD

04:15 PM Learning On-Device Conversational Models, Sujith Ravi

04:30 PM Google Lens, Hartwig Adam

05:00 PM Poster Spotlight 2 (list coming soon)

05:20 PM Poster Session 2

Farhan Shafiq, Antonio Tomas Nevado Vilchez, Takato Yamada, Sakyasingha Dasgupta, Robin Geyer, Moin Nabi, Crefeda Rodrigues, Edoardo Manino, Alexander Serb, Miguel A. Carreira-Perpinan, Kar Wai Lim, Bryan Kian Hsiang Low, Rohit Pandey, Marie C White, Pavel Pidlypenskyi, Xue Wang, Christine Kaeser-Chen, Michael Zhu, Suyog Gupta, Sam Leroux