This paper addresses the optimal rate allocation problem in overlay content distribution for efficient utilization of limited bandwidths. We systematically present a series of opti...
The problem of learning a sparse conic combination of kernel functions or kernel matrices for classification or regression can be achieved via the regularization by a block 1-norm...
Francis R. Bach, Romain Thibaux, Michael I. Jordan
Support Vector Machines (SVMs) are currently the state-of-the-art models for many classication problems but they suer from the complexity of their training algorithm which is at l...
Manifold learning can discover the structure of high dimensional data and provides understanding of multidimensional patterns by preserving the local geometric characteristics. Ho...
This paper presents three novel Moving Horizon Estimation (MHE) methods for discrete-time partitioned linear systems, i.e. systems decomposed into coupled subsystems with non-over...