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Model Compression: Bagging your Cake and Eating it too (part 1)

Model Compression: Bagging your Cake and Eating it too (part 1)

This video was recorded at NIPS Workshop on Efficient Machine Learning, Whistler 2007. The ever increasing size of available data to be processed by machine learning algorithms has yielded several approaches, from online algorithms to parallel and distributed computing on multi-node clusters. Nevertheless, it is not clear how modern machine learning approaches can either cope with such parallel machineries or take into account strong constraints regarding the available time to handle training and/or test examples. This workshop explores two alternatives: 1. modern machine learning approaches that can handle real time processing at train and/or at test time, under strict computational constraints (when the flow of incoming data is continuous and needs to be handled), and 2. modern machine... Show More


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