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» Sparse Kernel Regressors
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KDD
2004
ACM
181views Data Mining» more  KDD 2004»
15 years 10 months ago
Column-generation boosting methods for mixture of kernels
We devise a boosting approach to classification and regression based on column generation using a mixture of kernels. Traditional kernel methods construct models based on a single...
Jinbo Bi, Tong Zhang, Kristin P. Bennett
85
Voted
ICML
2008
IEEE
15 years 10 months ago
Sparse multiscale gaussian process regression
Most existing sparse Gaussian process (g.p.) models seek computational advantages by basing their computations on a set of m basis functions that are the covariance function of th...
Bernhard Schölkopf, Christian Walder, Kwang I...
ISCIS
2003
Springer
15 years 2 months ago
An Alternative Compressed Storage Format for Sparse Matrices
The handling of the sparse matrix vector product(SMVP) is a common kernel in many scientific applications. This kernel is an irregular problem, which has led to the development of...
Anand Ekambaram, Eurípides Montagne
PPSC
1997
14 years 11 months ago
Improving Memory-System Performance of Sparse Matrix-Vector Multiplication
Sparse matrix-vector multiplication is an important kernel that often runs inefficiently on superscalar RISC processors. This paper describes techniques that increase instruction-...
Sivan Toledo
ICANN
2003
Springer
15 years 2 months ago
Online Processing of Multiple Inputs in a Sparsely-Connected Recurrent Neural Network
The storage and short-term memory capacities of recurrent neural networks of spiking neurons are investigated. We demonstrate that it is possible to process online many superimpose...
Julien Mayor, Wulfram Gerstner