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159,162
A LinearTime Heuristic for Improving Network Partitions
, 1982
"... An iterative mincut heuristic for partitioning networks is presented whose worst case computation time, per pass, grows linearly with the size of the network. In practice, only a very small number of passes are typically needed, leading to a fast approximation algorithm for mincut partitioning. To d ..."
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Cited by 524 (0 self)
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An iterative mincut heuristic for partitioning networks is presented whose worst case computation time, per pass, grows linearly with the size of the network. In practice, only a very small number of passes are typically needed, leading to a fast approximation algorithm for mincut partitioning
Some methods for classification and analysis of multivariate observations
 In 5th Berkeley Symposium on Mathematical Statistics and Probability
, 1967
"... The main purpose of this paper is to describe a process for partitioning an Ndimensional population into k sets on the basis of a sample. The process, which is called 'kmeans, ' appears to give partitions which are reasonably ..."
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Cited by 3055 (3 self)
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The main purpose of this paper is to describe a process for partitioning an Ndimensional population into k sets on the basis of a sample. The process, which is called 'kmeans, ' appears to give partitions which are reasonably
Accurate Methods for the Statistics of Surprise and Coincidence
 COMPUTATIONAL LINGUISTICS
, 1993
"... Much work has been done on the statistical analysis of text. In some cases reported in the literature, inappropriate statistical methods have been used, and statistical significance of results have not been addressed. In particular, asymptotic normality assumptions have often been used unjustifiably ..."
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Cited by 1057 (1 self)
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Much work has been done on the statistical analysis of text. In some cases reported in the literature, inappropriate statistical methods have been used, and statistical significance of results have not been addressed. In particular, asymptotic normality assumptions have often been used
Learning to predict by the methods of temporal differences
 MACHINE LEARNING
, 1988
"... This article introduces a class of incremental learning procedures specialized for prediction – that is, for using past experience with an incompletely known system to predict its future behavior. Whereas conventional predictionlearning methods assign credit by means of the difference between predi ..."
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Cited by 1521 (56 self)
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, they have remained poorly understood. Here we prove their convergence and optimality for special cases and relate them to supervisedlearning methods. For most realworld prediction problems, temporaldifference methods require less memory and less peak computation than conventional methods and they produce
Casebased reasoning; Foundational issues, methodological variations, and system approaches
 AI COMMUNICATIONS
, 1994
"... Casebased reasoning is a recent approach to problem solving and learning that has got a lot of attention over the last few years. Originating in the US, the basic idea and underlying theories have spread to other continents, and we are now within a period of highly active research in casebased rea ..."
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Cited by 855 (25 self)
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, to which the subsequent descriptions and discussions will refer. The framework is influenced by recent methodologies for knowledge level descriptions of intelligent systems. The methods for case retrieval, reuse, solution testing, and learning are summarized, and their actual realization is discussed
Interior Point Methods in Semidefinite Programming with Applications to Combinatorial Optimization
 SIAM Journal on Optimization
, 1993
"... We study the semidefinite programming problem (SDP), i.e the problem of optimization of a linear function of a symmetric matrix subject to linear equality constraints and the additional condition that the matrix be positive semidefinite. First we review the classical cone duality as specialized to S ..."
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Cited by 547 (12 self)
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to SDP. Next we present an interior point algorithm which converges to the optimal solution in polynomial time. The approach is a direct extension of Ye's projective method for linear programming. We also argue that most known interior point methods for linear programs can be transformed in a
A case study of open source software development: the Apache server
 In: Proceedings of the 22nd International Conference on Software Engineering (ICSE 2000
, 2000
"... According to its proponents, open source style software development has the capacity to compete successfully, and perhaps in many cases displace, traditional commercial development methods. In order to begin investigating such claims, we examine the development process of a major open source applica ..."
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Cited by 806 (32 self)
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According to its proponents, open source style software development has the capacity to compete successfully, and perhaps in many cases displace, traditional commercial development methods. In order to begin investigating such claims, we examine the development process of a major open source
Discriminative Training Methods for Hidden Markov Models: Theory and Experiments with Perceptron Algorithms
, 2002
"... We describe new algorithms for training tagging models, as an alternative to maximumentropy models or conditional random fields (CRFs). The algorithms rely on Viterbi decoding of training examples, combined with simple additive updates. We describe theory justifying the algorithms through a modific ..."
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Cited by 660 (13 self)
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modification of the proof of convergence of the perceptron algorithm for classification problems. We give experimental results on partofspeech tagging and base noun phrase chunking, in both cases showing improvements over results for a maximumentropy tagger.
A Bayesian method for the induction of probabilistic networks from data
 MACHINE LEARNING
, 1992
"... This paper presents a Bayesian method for constructing probabilistic networks from databases. In particular, we focus on constructing Bayesian belief networks. Potential applications include computerassisted hypothesis testing, automated scientific discovery, and automated construction of probabili ..."
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Cited by 1400 (31 self)
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network from a database of cases. Finally, we relate the methods in this paper to previous work, and we discuss open problems.
The RungeKutta discontinuous Galerkin method for conservation laws V: multidimensional systems
, 1997
"... This is the fifth paper in a series in which we construct and study the socalled RungeKutta Discontinuous Galerkin method for numerically solving hyperbolic conservation laws. In this paper, we extend the method to multidimensional nonlinear systems of conservation laws. The algorithms are describ ..."
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Cited by 508 (44 self)
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This is the fifth paper in a series in which we construct and study the socalled RungeKutta Discontinuous Galerkin method for numerically solving hyperbolic conservation laws. In this paper, we extend the method to multidimensional nonlinear systems of conservation laws. The algorithms
Results 1  10
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159,162