Conveners
Industry talks and panel
- David Rousseau (LAL-Orsay, FR)
- Markus Stoye (CERN)
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Markus Stoye (CERN)15/04/2019, 14:00
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Dr Priya Ponnapalli (Amazon AI)15/04/2019, 14:20
The number of high-dimensional datasets recording multiple aspects of interrelated phenomena is increasing in many areas, from medicine to finance. This drives the need for mathematical frameworks that can simultaneously identify the similar and dissimilar among multiple matrices and tensors, and thus create a single coherent model from the multiple datasets. The generalized singular value...
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Dr Tim Genewein (DeepMind)15/04/2019, 15:05
Empirically it has been observed numerous times that trained neural networks often have high degrees of parameter-redundancy. It remains an open theoretical question why this parameter redundancy cannot be reduced before training by using smaller neural networks. On the other hand, the recent scientific literature reports a plethora of practical methods to "compress" neural networks during or...
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Dr Michel Herquet (B12)15/04/2019, 16:30
Machine Learning (and especially Deep Learning) algorithms often require large amounts of data to accomplish their tasks. However, a common problem when such approaches are applied in business contexts is that only relatively small datasets are initially accessible, leading to a fundamental question: how to apply ML tools when there is apparently not enough data available? In this talk, I will...
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Dr Michel Herquet (B12), Dr Tim Genewein (DeepMind)15/04/2019, 17:05
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