Friday, September 02, 2016

Nuit Blanche in Review (August 2016)

Much happened since the last Nuit Blanche in Review (July 2016): The big news this past August was the stellar line-up we got for a potential workshop at NIPS and the fact that it got declined  (There won't be a #NIPS2016 workshop on "Mapping Machine Learning to Hardware"). My take on this is that there is a surge of interest in mapping ML and even CS algorithms as close as possible to ASICs. That means that: either algorithms change because of the particular constraints of the silicon technology or that new technologies can be identified as important in the future. This problem is as much an industrial as an algorithmic one, so this type of workshop will eventually find its way in conferences like NIPS. In other words, it is not a question of "if" but "when". As a result of this, I created the MappingMLtoHardware tag that features either algorithmic effort to fit into hardware or hardware efforts to fit into particular classes of algorithms. On another front there is an exciting push for breaking the traditional backpropagation algorithm used for neural networks. Two different techniques were featured in [1and [2] this month. In the in-depth section, we noted a few uses for Random Features. We also had a long Paris Machine Learning Newsletter for this past Summer. Enjoy !

Implementations

We also created a new tag (Overviews) that features reviews, book and other material that provide some context. 

In-depth:



Hardware



Slides/videos:





CfP conference

Job:



Credit photo: NASA, APL, SwRI, 08-31-2016 Pluto's Methane Snowcaps on the Edge of Darkness

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