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Live Migration of Virtual Machines

by Christopher Clark, Keir Fraser, Steven H, Jakob Gorm Hansen, Eric Jul, Christian Limpach, Ian Pratt, Andrew Warfield - In Proceedings of the 2nd ACM/USENIX Symposium on Networked Systems Design and Implementation (NSDI , 2005
"... Migrating operating system instances across distinct physical hosts is a useful tool for administrators of data centers and clusters: It allows a clean separation between hardware and software, and facilitates fault management, load balancing, and low-level system maintenance. By carrying out the ma ..."
Abstract - Cited by 636 (15 self) - Add to MetaCart
Migrating operating system instances across distinct physical hosts is a useful tool for administrators of data centers and clusters: It allows a clean separation between hardware and software, and facilitates fault management, load balancing, and low-level system maintenance. By carrying out

A learning algorithm for Boltzmann machines

by H. Ackley, E. Hinton, J. Sejnowski - Cognitive Science , 1985
"... The computotionol power of massively parallel networks of simple processing elements resides in the communication bandwidth provided by the hardware connections between elements. These connections con allow a significant fraction of the knowledge of the system to be applied to an instance of a probl ..."
Abstract - Cited by 584 (13 self) - Add to MetaCart
. Second, there must be some way of choosing internal representations which allow the preexisting hardware connections to be used efficiently for encoding the con-straints in the domain being searched. We describe a generol parallel search method, based on statistical mechanics, and we show how it leads

Machine Learning in Automated Text Categorization

by Fabrizio Sebastiani - ACM COMPUTING SURVEYS , 2002
"... The automated categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last ten years, due to the increased availability of documents in digital form and the ensuing need to organize them. In the research community the dominant approach to this p ..."
Abstract - Cited by 1734 (22 self) - Add to MetaCart
to this problem is based on machine learning techniques: a general inductive process automatically builds a classifier by learning, from a set of preclassified documents, the characteristics of the categories. The advantages of this approach over the knowledge engineering approach (consisting in the manual

Laplacian Eigenmaps for Dimensionality Reduction and Data Representation

by Mikhail Belkin, Partha Niyogi , 2003
"... One of the central problems in machine learning and pattern recognition is to develop appropriate representations for complex data. We consider the problem of constructing a representation for data lying on a low-dimensional manifold embedded in a high-dimensional space. Drawing on the correspondenc ..."
Abstract - Cited by 1226 (15 self) - Add to MetaCart
One of the central problems in machine learning and pattern recognition is to develop appropriate representations for complex data. We consider the problem of constructing a representation for data lying on a low-dimensional manifold embedded in a high-dimensional space. Drawing

Inductive learning algorithms and representations for text categorization,”

by Susan Dumais , John Platt , Mehran Sahami , David Heckerman - in Proceedings of the International Conference on Information and Knowledge Management, , 1998
"... ABSTRACT Text categorization -the assignment of natural language texts to one or more predefined categories based on their content -is an important component in many information organization and management tasks. We compare the effectiveness of five different automatic learning algorithms for text ..."
Abstract - Cited by 652 (8 self) - Add to MetaCart
categorization in terms of learning speed, realtime classification speed, and classification accuracy. We also examine training set size, and alternative document representations. Very accurate text classifiers can be learned automatically from training examples. Linear Support Vector Machines (SVMs

Maté: A Tiny Virtual Machine for Sensor Networks

by Philip Levis, David Culler , 2002
"... Composed of tens of thousands of tiny devices with very limited resources ("motes"), sensor networks are subject to novel systems problems and constraints. The large number of motes in a sensor network means that there will often be some failing nodes; networks must be easy to repopu-late. ..."
Abstract - Cited by 510 (21 self) - Add to MetaCart
capsules enable the deploy-ment of ad-hoc routing and data aggregation algorithms. Maté's concise, high-level program representation simplifies programming and allows large networks to be frequently re-programmed in an energy-efficient manner; in addition, its safe execution environment suggests a use

Scale and performance in a distributed file system

by John H. Howard, Michael L. Kazar, Sherri G. Menees, A. Nichols, M. Satyanarayanan, Robert N. Sidebotham, Michael J. West - ACM Transactions on Computer Systems , 1988
"... The Andrew File System is a location-transparent distributed tile system that will eventually span more than 5000 workstations at Carnegie Mellon University. Large scale affects performance and complicates system operation. In this paper we present observations of a prototype implementation, motivat ..."
Abstract - Cited by 933 (45 self) - Add to MetaCart
, motivate changes in the areas of cache validation, server process structure, name translation, and low-level storage representation, and quantitatively demonstrate Andrew’s ability to scale gracefully. We establish the importance of whole-file transfer and caching in Andrew by comparing its performance

LLVM: A compilation framework for lifelong program analysis & transformation

by Chris Lattner, Vikram Adve , 2004
"... ... a compiler framework designed to support transparent, lifelong program analysis and transformation for arbitrary programs, by providing high-level information to compiler transformations at compile-time, link-time, run-time, and in idle time between runs. LLVM defines a common, low-level code re ..."
Abstract - Cited by 852 (20 self) - Add to MetaCart
... a compiler framework designed to support transparent, lifelong program analysis and transformation for arbitrary programs, by providing high-level information to compiler transformations at compile-time, link-time, run-time, and in idle time between runs. LLVM defines a common, low-level code

Exokernel: An Operating System Architecture for Application-Level Resource Management

by Dawson R. Engler, M. Frans Kaashoek, James O’toole , 1995
"... We describe an operating system architecture that securely multiplexes machine resources while permitting an unprecedented degree of application-specific customization of traditional operating system abstractions. By abstracting physical hardware resources, traditional operating systems have signifi ..."
Abstract - Cited by 732 (24 self) - Add to MetaCart
that includes Aegis, an exokernel, and ExOS, an untrusted application-level operating system. Aegis defines the low-level interface to machine resources. Applications can allocate and use machine resources, efficiently handle events, and participate in resource revocation. Measurements show that most primitive

Graphical models, exponential families, and variational inference

by Martin J. Wainwright, Michael I. Jordan , 2008
"... The formalism of probabilistic graphical models provides a unifying framework for capturing complex dependencies among random variables, and building large-scale multivariate statistical models. Graphical models have become a focus of research in many statistical, computational and mathematical fiel ..."
Abstract - Cited by 819 (28 self) - Add to MetaCart
fields, including bioinformatics, communication theory, statistical physics, combinatorial optimization, signal and image processing, information retrieval and statistical machine learning. Many problems that arise in specific instances — including the key problems of computing marginals and modes
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