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Conventional linear subspace learning methods like principal component analysis (PCA), linear discriminant analysis (LDA) derive subspaces from the whole data set. These approaches have limitations in the sense that they are linear while the data distribut ...
Institute of Electrical and Electronics Engineers2011
Ten years ago, PLSI opened the road to probabilistic latent semantic representations of documents. It led to a number of applications in different fields, including ad hoc Information Retrieval. However, inherent limitations hinder its use on documents not ...
Springer-Verlag New York, Ms Ingrid Cunningham, 175 Fifth Ave, New York, Ny 10010 Usa2009
Commercial server applications remain memory bound on modern multiprocessor systems because of their large data footprints, frequent sharing, complex non-strided access patterns, and long chains of dependant misses. To improve memory system performance des ...
The Support Vector Machine (SVM) is an acknowledged powerful tool for building classifiers, but it lacks flexibility, in the sense that the kernel is chosen prior to learning. Multiple Kernel Learning (MKL) enables to learn the kernel, from an ensemble of ...
The Support Vector Machine (SVM) is an acknowledged powerful tool for building classifiers, but it lacks flexibility, in the sense that the kernel is chosen prior to learning. Multiple Kernel Learning (MKL) enables to learn the kernel, from an ensemble of ...
We propose a semiparametric model for regression problems involving multiple response variables. Conditional dependencies between the responses are represented through a linear mixture of Gaussian processes. We propose an efficient approximate inference sc ...
We show that for a voter model on {0,1}Z corresponding to a random walk with kernel p(·) and starting from unanimity to the right and opposing unanimity to the left, a tight interface between 0's and 1's exists if p(·) has second moments but does not if p( ...
We propose a highly efficient framework for kernel multi-class models with a large and structured set of classes. Kernel parameters are learned automatically by maximizing the cross-validation log likelihood, and predictive probabilities are estimated. We ...
This paper presents an efficient integral-equation (IE) technique for analysis of thick irises inside multilayered rectangular waveguides. The IEs remain the same as in the case of zero-thickness iris and the thickness is accounted for only as a correction ...
Most operating systems enforce process isolation through hardware protection mechanisms such as memory segmentation, page mapping, and differentiated user and kernel instructions. Singularity is a new operating system that uses software mechanisms to enfor ...
