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316,432
On µkernel construction
 Symposium on Operating System Principles
, 1995
"... From a softwaretechnology point of view, thekernel concept is superior to large integrated kernels. On the other hand, it is widely believed that (a)kernel based systems are inherently inefficient and (b) they are not sufficiently flexible. Contradictory to this belief, we show and support by doc ..."
Abstract

Cited by 424 (25 self)
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From a softwaretechnology point of view, thekernel concept is superior to large integrated kernels. On the other hand, it is widely believed that (a)kernel based systems are inherently inefficient and (b) they are not sufficiently flexible. Contradictory to this belief, we show and support
On�kernel construction
 In SOSP. ACM
, 1995
"... From a softwaretechnology point of view, thekernel concept is superior to large integrated kernels. On the other hand, it is widely believed that (a)kernel based systems are inherently ine cient and (b) they are not su ciently exible. Contradictory to this belief, we show and support by documenta ..."
Abstract

Cited by 5 (1 self)
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From a softwaretechnology point of view, thekernel concept is superior to large integrated kernels. On the other hand, it is widely believed that (a)kernel based systems are inherently ine cient and (b) they are not su ciently exible. Contradictory to this belief, we show and support
On μKernel Construction
, 1995
"... From a softwaretechnology point of view, the µkernel concept is superior to large integrated kernels. On the other hand, it is widely believed that (a) µkernel based systems are inherently inefficient and (b) they are not sufficiently flexible. Contradictory to this belief, we show and support by ..."
Abstract

Cited by 1 (0 self)
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From a softwaretechnology point of view, the µkernel concept is superior to large integrated kernels. On the other hand, it is widely believed that (a) µkernel based systems are inherently inefficient and (b) they are not sufficiently flexible. Contradictory to this belief, we show and support
Abstract On pKernel Construction
"... From a softwaretechnology point of view, the pkernel concept is superior to large integrated kernels. On the other hand, it is widely believed that (a) pkernel based systems are inherently inefficient and (b) they are not sufficiently flexible. Contradictory to this belief, we show and support by ..."
Abstract
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From a softwaretechnology point of view, the pkernel concept is superior to large integrated kernels. On the other hand, it is widely believed that (a) pkernel based systems are inherently inefficient and (b) they are not sufficiently flexible. Contradictory to this belief, we show and support
Convolution Kernels on Discrete Structures
, 1999
"... We introduce a new method of constructing kernels on sets whose elements are discrete structures like strings, trees and graphs. The method can be applied iteratively to build a kernel on an infinite set from kernels involving generators of the set. The family of kernels generated generalizes the fa ..."
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Cited by 510 (0 self)
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We introduce a new method of constructing kernels on sets whose elements are discrete structures like strings, trees and graphs. The method can be applied iteratively to build a kernel on an infinite set from kernels involving generators of the set. The family of kernels generated generalizes
Fisher Discriminant Analysis With Kernels
, 1999
"... A nonlinear classification technique based on Fisher's discriminant is proposed. The main ingredient is the kernel trick which allows the efficient computation of Fisher discriminant in feature space. The linear classification in feature space corresponds to a (powerful) nonlinear decision f ..."
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Cited by 493 (18 self)
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A nonlinear classification technique based on Fisher's discriminant is proposed. The main ingredient is the kernel trick which allows the efficient computation of Fisher discriminant in feature space. The linear classification in feature space corresponds to a (powerful) nonlinear decision
The xKernel: An Architecture for Implementing Network Protocols
 IEEE Transactions on Software Engineering
, 1991
"... This paper describes a new operating system kernel, called the xkernel, that provides an explicit architecture for constructing and composing network protocols. Our experience implementing and evaluating several protocols in the xkernel shows that this architecture is both general enough to acc ..."
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Cited by 663 (21 self)
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This paper describes a new operating system kernel, called the xkernel, that provides an explicit architecture for constructing and composing network protocols. Our experience implementing and evaluating several protocols in the xkernel shows that this architecture is both general enough
Nonlinear component analysis as a kernel eigenvalue problem

, 1996
"... We describe a new method for performing a nonlinear form of Principal Component Analysis. By the use of integral operator kernel functions, we can efficiently compute principal components in highdimensional feature spaces, related to input space by some nonlinear map; for instance the space of all ..."
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Cited by 1554 (85 self)
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We describe a new method for performing a nonlinear form of Principal Component Analysis. By the use of integral operator kernel functions, we can efficiently compute principal components in highdimensional feature spaces, related to input space by some nonlinear map; for instance the space of all
Learning the Kernel Matrix with SemiDefinite Programming
, 2002
"... Kernelbased learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is performed implicitly, by specifying the inner products between each pair of points in the embedding space. This information ..."
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Cited by 780 (22 self)
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Kernelbased learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is performed implicitly, by specifying the inner products between each pair of points in the embedding space. This information
The pyramid match kernel: Discriminative classification with sets of image features
 IN ICCV
, 2005
"... Discriminative learning is challenging when examples are sets of features, and the sets vary in cardinality and lack any sort of meaningful ordering. Kernelbased classification methods can learn complex decision boundaries, but a kernel over unordered set inputs must somehow solve for correspondenc ..."
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Cited by 546 (29 self)
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Discriminative learning is challenging when examples are sets of features, and the sets vary in cardinality and lack any sort of meaningful ordering. Kernelbased classification methods can learn complex decision boundaries, but a kernel over unordered set inputs must somehow solve
Results 1  10
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316,432