Sunday, July 31, 2016

Nuit Blanche in Review (July 2016)

Much happened this past month since the last Nuit Blanche in Review (June 2016). We submitted a proposal for a two day workshop at NIPS on "Mapping Machine Learning to Hardware" (the list of proposed speakers is included in the post), we featured two proofs on the same problem from two different groups (the third proof being on a different problem altogether), one implementation, a survey and a video on randomized methods, some exciting results on random projections in manifolds and in practice with deep learning, a continuing set of posts showing the Great Convergence in action, a few applications centered posts and much more.... Enjoy. In the meantime, the image above shows the current state of reactor 2 at Fukushima Daiichi. That image uses Muon tomography and a reconstruction algorithm we mentioned back in Imaging Damaged Reactors and Volcanoes. Without further ado.


Hardware and related
Random Projections
Random Features
Connection between compressive sensing and Deep Learning
AMP/FrankWolfe/ Hashing/Deep Learning
Application centered


 Credit photo: TEPCO
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