2nd Workshop on Embedded Machine Learning - WEML2018

Heidelberg University, Nov 8, 2018

INF306, SR14 (ground level)

Holger Fröning, ZITI, Heidelberg University, Germany

Franz Pernkopf, Graz University of Technology, Austria

Manfred Mücke, Materials Center Leoben, Leoben, Austria

In November 2018, our second Workshop on Embedded Machine (WEML) took place in Heidelberg, Germany. We received a nice attendance of more than 30 people interested in the broad topic of applying machine learning methods to embedded systems. Speakers and talks were as follows:

Schedule

13:00 - 13:15 Holger Fröning/Heidelberg University: Introduction
13:15 - 13:50 Günther Schindler, Holger Fröning/Heidelberg University: The DeepChip Software Architecture
13:50 - 14:25 Wolfgang Roth, Franz Pernkopf/Graz University of Technology: Bayesian networks and PGMs
14:25 - 15:00 Christoph Gratl, Manfred Mücke/Materials Center Leoben: Investigating data-type propagation in Tensorflow/XLA-AOT/LLVM for ARM v7 architectures
15:00 - 15:45 Coffee break
15:45 - 16:20 Robert Peharz/Cambridge: Minimal Random Code Learning: Getting Bits Back from Compressed Model Parameters
16:20 - 16:55 Nick Fraser/Xilinx Ireland: Training Methods For Reduced Precision Neural Networks
16:55 - 17:30 Peter Zaspel/Basel University: Augmenting the explanatory power of predictions by uncertainty quantification
17:30 - 18:05 Jonas Große Sundrup/Heidelberg University: Towards embedded Machine Learning for motion classification in patient monitoring systems
18:05 - 18:20 Concluding discussion

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