SAP
Event Program
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Time

Session

9:00 – 9:30

Welcome Coffee & Snacks

 

 

9:30 – 9:50

Introduction & Opening Remarks

Zbigniew Jerzak

 

 

10:00 – 10:30

Enhancing Multi-task Learning with Fairness and Privacy Constraints

Massimiliano Pontil - University College London & Instituto Italiano Di Technologia

 

 

10:35 – 11:05

Deep Learning for Modeling Neuroimaging Data

Christian Wachinger – Ludwig Maximilian University of Munich

 

 

11:05 – 11:50

Break + Poster Presentations

 

 

11:50 – 12:20

Extracting and Modeling Relations with Graph Convolutional Networks

Ivan Titov - University of Edinburgh & University of Amsterdam

 

 

12:25 – 12:55

Deep Learning with Deep Knowledge

Volker Tresp - Ludwig Maximilian University of Munich & Siemens

 

 

12:55 – 14:00

Lunch Break

 

 

14:00– 14:30

Deep Networks with Dense Connectivity

Kilian Weinberger - Cornell University

 

 

14:35 – 15:05

Efficient and Accurate CNN Models at Edge Compute Platforms

Mohammad Rastegari - Allen Institute for Artificial Intelligence

 

 

15:10 – 15:40

Feedback Propagation in Deep Neural Networks

Vicente Ordóñez Román - University of Virginia

 

 

15:40 – 16:20

Break + Poster Presentations

 

 

16:20 – 16:50

Generative-Discriminative Multi-Modal Learning

Kayhan Batmanghelich - University of Pittsburgh & Carnegie Mellon University

 

 

16:55 – 17:25

Self-supervised Learning for Visual Recognition

Hamed Pirsiavash - University of Maryland, Baltimore County

 

 

17:25 – 17:40

Closing Remarks

 

 

17:40 – 18:30

Networking + Poster Presentations

 

 

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Presentations Slides
Feedback Propagation in Deep Neural Networks - Vicente Ordóñez Román
Dense Networks with Dense Connectivity - Kilian Weinberger
Self-supervised Learning for Visual Recognition - Hamed Pirsiavash
Generative-Discriminative Multi-Modal Learning - Kayhan Batmanghelich
Extracting and Modeling Relations with Graph Convolutional Networks - Ivan Titov
Deep Learning with Deep Knowledge - Volker Tresp
Enhancing Multitask Learning with Fairness and Privacy Constraints - Massimiliano Pontil
Efficient and Accurate CNN Models at Edge Compute Platforms - Mohammad Rastegari
Invited Speakers
Massimiliano Pontil
University College London & Instituto Italiano Di Technologia
Christian Wachinger
Ludwig Maximilian University of Munich
Ivan Titov
University of Edinburgh & University of Amsterdam
Volker Tresp
Ludwig Maximilian University of Munich
Kilian Weinberger
Cornell University
Mohammad Rastegari
Allen Institute for Artificial Intelligence
Vicente Ordóñez Román
University of Virginia
Kayhan Batmanghelich
University of Pittsburgh & Carnegie Mellon University
Hamed Pirsiavash
University of Maryland, Baltimore Country