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Results 1 - 10
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4,205
Scaling Kernel-Based Systems to Large Data Sets
- Data Mining and Knowledge Discovery
, 2001
"... . In the form of the support vector machine and Gaussian processes, kernel-based systems are currently very popular approaches to supervised learning. Unfortunately, the computational load for training kernel-based systems increases drastically with the size of the training data set, such that these ..."
Abstract
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Cited by 13 (1 self)
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. In the form of the support vector machine and Gaussian processes, kernel-based systems are currently very popular approaches to supervised learning. Unfortunately, the computational load for training kernel-based systems increases drastically with the size of the training data set
The performance of µ-kernel-based systems
- In 16 th ACM Symposium on Operating Systems Principles
, 1997
"... First-generation µ-kernels have a reputation for being too slow and lacking sufficient flexibility. To determine whether L4, a lean second-generation µ-kernel, has overcome these limitations, we have repeated several earlier experiments and conducted some novel ones. Moreover, we ported the Linux op ..."
Abstract
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Cited by 148 (17 self)
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operating system to run on top of the L4 µ-kernel and compared the resulting system with both Linux running native, and MkLinux, a Linux version that executes on top of a first-generation Mach-derived µ-kernel. For L4Linux, the AIM benchmarks report a maximum throughput which is only 5 % lower than
A-Posteriori Error Estimation for Parameterized Kernel-Based Systems?
"... Abstract: This work is concerned with derivation of fully offline/online decomposable efficient a-posteriori error estimators for reduced parameterized nonlinear kernel-based systems. The dynamical systems under consideration consist of a nonlinear, time- and parameter-dependent kernel expansion rep ..."
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Abstract: This work is concerned with derivation of fully offline/online decomposable efficient a-posteriori error estimators for reduced parameterized nonlinear kernel-based systems. The dynamical systems under consideration consist of a nonlinear, time- and parameter-dependent kernel expansion
Abstract The Performance of p-Kernel-Based Systems
"... First-generation p-kernels have a reputation for being too slow and lacking sufficient flexibility. To determine whether LA, a lean second-generation p-kernel, has overcome these limitations, we have repeated several earlier experiments and conducted some novel ones. Moreover, we ported the Linux op ..."
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operating system to run on top of the L4 p-kernel and compared the resulting system with both Linux running native, and MkLinux, a Linux version that executes on top of a first-generation Mach-derived p-kernel. For L4Linux, the AIM benchmarks report a maximum through-put which is only 5 % lower than
On a µ-Kernel Based System Architecture Enabling Recovery from Rootkits
"... We present a system architecture called spine that supports detection and recovery from many kernel-level and user-level rootkits. The architecture forms a reliable basis for an intrusion recovery system (IRS). The spine architecture is a multi-tiered approach, relying on the integrity of a small µ- ..."
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We present a system architecture called spine that supports detection and recovery from many kernel-level and user-level rootkits. The architecture forms a reliable basis for an intrusion recovery system (IRS). The spine architecture is a multi-tiered approach, relying on the integrity of a small µ-kernel
Implementation of an Orthogonally Persistent L4 �-Kernel Based System
, 2002
"... Orthogonal persistent systems open up possibilities for a wide number of applications. Even more, it is a very natural concept for the storage of information, since objects and information persists until the end of their lifetime. Most current commercial non-persistent systems have only an explicit ..."
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, persistent storage could be handled implicitly by the operating system. The operating system has to store for each task an image of the user memory and all kernel internal data like pagetables,
Implementation of an Orthogonally Persistent L4 µ-Kernel Based System
"... Orthogonal persistent systems open up possibilities for a wide number of applications. Even more, it is a very natural concept for the storage of information, since objects and information persists until the end of their lifetime. Most current commercial non-persistent systems have only an explicit ..."
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Orthogonal persistent systems open up possibilities for a wide number of applications. Even more, it is a very natural concept for the storage of information, since objects and information persists until the end of their lifetime. Most current commercial non-persistent systems have only an explicit
16th ACM Symposium on Operating Systems Principles (SOSP ’97), October 5–8, 1997, Saint-Malo, France The Performance of µ-Kernel-Based Systems
"... First-generation µ-kernels have a reputation for being too slow and lacking sufficient flexibility. To determine whether L4, a lean second-generation µ-kernel, has overcome these limitations, we have repeated several earlier experiments and conducted some novel ones. Moreover, we ported the Linux op ..."
Abstract
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operating system to run on top of the L4 µ-kernel and compared the resulting system with both Linux running native, and MkLinux, a Linux version that executes on top of a firstgeneration Mach-derived µ-kernel. For L 4 Linux, the AIM benchmarks report a maximum throughput which is only 5 % lower than
On µ-kernel construction
- Symposium on Operating System Principles
, 1995
"... From a software-technology point of view, the-kernel 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
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Cited by 429 (25 self)
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From a software-technology point of view, the-kernel 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
Scalable Kernel Systems
"... Kernel-based systems are currently very popular approaches to supervised learning. Unfortunately, the computational load for training kernel-based systems increases drastically with the number of training data points. Recently, a number of approximate methods for scaling kernel-based systems to larg ..."
Abstract
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Cited by 7 (2 self)
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Kernel-based systems are currently very popular approaches to supervised learning. Unfortunately, the computational load for training kernel-based systems increases drastically with the number of training data points. Recently, a number of approximate methods for scaling kernel-based systems
Results 1 - 10
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4,205
