*Ichino, M.[Manabu]*,
*Sklansky, J.[Jack]*,

**The relative neighborhood graph for mixed feature variables**,

*PR(18)*, No. 2, 1985, pp. 161-167.

Elsevier DOI
**0309**

BibRef

*Fränti, P.[Pasi]*,
*Virmajoki, O.[Olli]*,

**Iterative shrinking method for clustering problems**,

*PR(39)*, No. 5, May 2006, pp. 761-775.

Elsevier DOI Vector quantization; Codebook generation; Agglomeration; PNN
**0604**

BibRef

Earlier: A2, A1:

**Divide-and-conquer algorithm for creating neighborhood graph for
clustering**,

*ICPR04*(I: 264-267).

IEEE DOI
**0409**

BibRef

*Virmajoki, O.*,
*Franti, P.*,
*Kaukoranta, T.*,

**Iterative shrinking method for generating clustering**,

*ICIP02*(II: 685-688).

IEEE DOI
**0210**

BibRef

*Wen, G.H.[Gui-Hua]*,
*Jiang, L.J.[Li-Jun]*,
*Wen, J.[Jun]*,

**Using locally estimated geodesic distance to optimize neighborhood
graph for isometric data embedding**,

*PR(41)*, No. 7, July 2008, pp. 2226-2236.

Elsevier DOI
**0804**

BibRef

And:
Authors' response:
*PR(42)*, No. 5, May 2009, pp. 1014.

Elsevier DOI
**0902**

Isometric data embedding; Nonlinear neighborhood; Neighborhood graph;
Geodesic distance; Manifold learning
BibRef

*Wen, G.H.[Gui-Hua]*,
*Jiang, L.J.[Li-Jun]*,
*Wen, J.[Jun]*,

**Local relative transformation with application to isometric embedding**,

*PRL(30)*, No. 3, 1 February 2009, pp. 203-211.

Elsevier DOI
**0804**

Isometric embedding; Cognitive law; Relative transformation;
Local relative transformation; Neighborhood graph; Manifold learning
BibRef

*Zhong, C.M.[Cai-Ming]*,
*Miao, D.Q.[Duo-Qian]*,

**A comment on 'Using locally estimated geodesic distance to optimize
neighborhood graph for isometric data embedding'**,

*PR(42)*, No. 5, May 2009, pp. 1012-1013.

Elsevier DOI
**0902**

Triangle inequality; Geodesic distance; Euclidean distance
See also Using locally estimated geodesic distance to optimize neighborhood graph for isometric data embedding.
BibRef

*Meng, D.Y.[De-Yu]*,
*Leung, Y.[Yee]*,
*Xu, Z.B.[Zong-Ben]*,
*Fung, T.[Tung]*,
*Zhang, Q.F.[Qing-Fu]*,

**Improving geodesic distance estimation based on locally linear
assumption**,

*PRL(29)*, No. 7, 1 May 2008, pp. 862-870.

Elsevier DOI
**0804**

Isometric feature mapping; Geodesic distance estimation;
Neighborhood graph; Nonlinear dimensionality reduction
BibRef

*Yang, Y.[Yi]*,
*Han, D.Q.[De-Qiang]*,
*Dezert, J.[Jean]*,

**An angle-based neighborhood graph classifier with evidential
reasoning**,

*PRL(71)*, No. 1, 2016, pp. 78-85.

Elsevier DOI
**1602**

Neighborhood classifier
BibRef

Springer DOI

BibRef

*Wang, J.[Jing]*,
*Wang, J.D.[Jing-Dong]*,
*Zeng, G.[Gang]*,
*Gan, R.[Rui]*,
*Li, S.P.[Shi-Peng]*,
*Guo, B.[Baining]*,

**Fast Neighborhood Graph Search Using Cartesian Concatenation**,

*ICCV13*(2128-2135)

IEEE DOI
**1403**

new data structure for approximate nearest neighbor search
BibRef

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in

Optimal Path Forest Classification .

Last update:Feb 20, 2020 at 21:34:09