Skip to search formSkip to main content

You are currently offline. Some features of the site may not work correctly.

Semantic Scholar uses AI to extract papers important to this topic.

Highly Cited

2008

Highly Cited

2008

We consider the problem of estimating the parameters of a Gaussian or binary distribution in such a way that the resulting… Expand

Is this relevant?

Highly Cited

2007

Highly Cited

2007

Abstract Eigenvectors, and the related centrality measure Bonacich's c(β), have advantages over graph-theoretic measures like… Expand

Is this relevant?

Highly Cited

2005

Highly Cited

2005

Clustering is the problem of identifying the distribution of patterns and intrinsic correlations in large data sets by… Expand

Is this relevant?

Highly Cited

2002

Highly Cited

2002

The problem of choosing the correct number of clusters is as old as cluster analysis itself. A number of authors have suggested… Expand

Is this relevant?

Highly Cited

1995

Highly Cited

1995

From the Publisher:
Artificial "neural networks" are now widely used as flexible models for regression classification… Expand

Is this relevant?

Highly Cited

1993

Highly Cited

1993

Marginal models for multivariate binary data permit separate modelling of the relationship of the response with explanatory… Expand

Is this relevant?

Highly Cited

1993

Highly Cited

1993

A new class of convolutional codes called turbo-codes, whose performances in terms of bit error rate (BER) are close to the… Expand

Is this relevant?

Highly Cited

1993

Highly Cited

1993

Highly Cited

1993

A circuit implementation of the chaotic Lorenz system is described. The chaotic behavior of the circuit closely matches the… Expand

Is this relevant?

Highly Cited

1971