Technical Program (BST time zone)

13:50 - 14:00 Welcome and Opening Remarks
                      Stylianos I. Venieris (Samsung AI)

14:00 - 14:45 Keynote 1
Session Chair: Nic Lane (Samsung AI, University of Cambridge)

          

14:45 - 15:30 Session 1
Session Chair: Yunxin Liu (Microsoft Research)

     
Hybrid Fusion Learning: A Hierarchical Learning Model For Distributed Systems  
Anirudh Kasturi, Anish Reddy Ellore, Paresh Saxena, Chittaranjan Hota (BITS Pilani)
Full presentation

     
Split Computing for Complex Object Detectors: Challenges and Preliminary Results  
Yoshitomo Matsubara, Marco Levorato (University of California, Irvine)
Full presentation

15.30 - 16.15 Keynote 2
Session Chair: Marco Gruteser (Google, Rutgers University)

          

16.15 - 17.00 Session 2
Session Chair: Hyeji Kim (University of Texas at Austin)

     
Classifying WLAN Packets from the RF Envelope: Towards More Efficient Wireless Network Performance  
Zerina Kapetanovic, Gregory E. Moore, Shanti Garman, Joshua R. Smith (University of Washington)
Full presentation

     
Amplitude Suppression and Direction Activation in Networks for 1-bit Faster R-CNN  
Sheng Xu, Zhendong Liu, Xuan Gong, Chunlei Liu, Mingyuan Mao, Baochang Zhang (Beihang University)
Full presentation

17.00 - 17.45 Keynote 3
Session Chair: Stylianos I. Venieris (Samsung AI)

          

17.45 - 18.30 Panel Discussion
Chair: Stylianos I. Venieris (Samsung AI)

    Themes:

  • Cross-stack Deployability Challenges for Federated Learning  
  • The Interplay between DNN and Processor Design  

Christos Bouganis
(Imperial College London)

Koen Helwegen
(Plumerai)

Aruna Balasubramanian
(Stony Brook University)

Poonam Yadav
(University of York, UK)

18.30 - 19.15 TensorFlow Federated (TFF) Tutorial
Chairs: Emily Glanz (Google), Weikang Song (Google)