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Review

2019

Review

2019

Research into self-regulated learning has traditionally relied upon self-reported data. While there is a rich body of literature… Expand

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Highly Cited

2010

Highly Cited

2010

With every graph (or digraph) one can associate several different matrices. We have already seen the vertex-edge incidence matrix… Expand

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Highly Cited

2009

Highly Cited

2009

We propose a novel method for constructing wavelet transforms of functions defined on the vertices of an arbitrary finite… Expand

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Highly Cited

2009

Highly Cited

2009

The modern science of networks has brought significant advances to our understanding of complex systems. One of the most relevant… Expand

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Highly Cited

2008

Highly Cited

2008

Graph theory is a flourishing discipline containing a body of beautiful and powerful theorems of wide applicability. Its… Expand

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Highly Cited

2002

Highly Cited

2002

The application of kernel-based learning algorithms has, so far, largely been confined to realvalued data and a few special data… Expand

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Highly Cited

2000

Highly Cited

2000

We propose a random graph model which is a special case of sparse random graphs with given degree sequences. This model involves… Expand

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Highly Cited

1991

Highly Cited

1991

SUMMARY We present a modification of the spring-embedder model of Eades [ Congresses Numerantium, 42, 149–160, (1984)] for… Expand

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Highly Cited

1986

Highly Cited

1986

In this paper we present a new data structure for representing Boolean functions and an associated set of manipulation algorithms… Expand

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Highly Cited

1959

Highly Cited

1959

We consider n points (nodes), some or all pairs of which are connected by a branch; the length of each branch is given. We… Expand

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