

Wasserstein gradient flows and applications to sampling in machine learning - lecture 1
De Anna Korba


Wasserstein gradient flows and applications to sampling in machine learning - lecture 2
De Anna Korba
De Yuchong Hu
Apparaît dans la collection : 2016 - T1 - WS2 - Fundamental inequalities and lower bounds theme
Inter-cloud (or Cloud of Clouds) is viewed as the next revolution in the cloud computing paradigm wherein the computational and data infrastructure for handling scientific,business and enterprise applications spans across multi-type and multi-brand clouds, and inter-cloud storage is exactly one of key parts of inter-cloud. Due to high transmission cost among inter-cloud storage nodes, it makes the difficulty of promotion for inter-cloud storage. However, it lacks efficient schemes to reduce the bandwidth cost consuming by system operations of inter-cloud storage. Motivated by this, we start our studies based on inter-cloud storage, use the information flow graph and product-matrix framework as the main modeling methodologies, adopt random linear network coding as the main technique, and study some key issues of inter-cloud storage.