14.2.14.2 Archetypal Analysis

Chapter Contents (Back)
Archetypal Analysis.

Seth, S.[Sohan], Eugster, M.J.A.[Manuel J. A.],
Archetypal Analysis for Nominal Observations,
PAMI(38), No. 5, May 2016, pp. 849-861.
IEEE DOI 1604
explains a set of observations as compositions of few pure patterns. Bayes methods BibRef

Ni, D., Ma, H.,
Fast Classification of Hyperspectral Images Using Globally Regularized Archetypal Representation With Approximate Solution,
GeoRS(55), No. 4, April 2017, pp. 2414-2430.
IEEE DOI 1704
approximation theory BibRef

Sun, W.W.[Wei-Wei], Zhang, D.[Dianfa], Xu, Y.[Yan], Tian, L.[Long], Yang, G.[Gang], Li, W.[Weiyue],
A Probabilistic Weighted Archetypal Analysis Method with Earth Mover's Distance for Endmember Extraction from Hyperspectral Imagery,
RS(9), No. 8, 2017, pp. xx-yy.
DOI Link 1708
BibRef

Sun, W.W.[Wei-Wei], Yang, G.[Gang], Wu, K.[Ke], Li, W.Y.[Wei-Yue], Zhang, D.[Dianfa],
Pure endmember extraction using robust kernel archetypoid analysis for hyperspectral imagery,
PandRS(131), No. 1, 2017, pp. 147-159.
Elsevier DOI 1709
Endmember, extraction BibRef


Keller, S.M.[Sebastian Mathias], Samarin, M.[Maxim], Wieser, M.[Mario], Roth, V.[Volker],
Deep Archetypal Analysis,
GCPR19(171-185).
Springer DOI 1911
Representations of high-dimensional datasets in terms of intuitively understandable basic entities called archetypes. BibRef

Mei, J.[Jieru], Wang, C.Y.[Chun-Yu], Zeng, W.J.[Wen-Jun],
Online Dictionary Learning for Approximate Archetypal Analysis,
ECCV18(III: 501-516).
Springer DOI 1810
BibRef

Fotiadou, E.[Eftychia], Panagakis, Y.[Yiannis], Pantic, M.[Maja],
Temporal Archetypal Analysis for Action Segmentation,
FG17(490-496)
IEEE DOI 1707
Convergence, Data mining, Feature extraction, Optimization, Symmetric matrices, Time series analysis, Visualization BibRef

Bauckhage, C.[Christian], Manshaei, K.[Kasra],
Kernel Archetypal Analysis for Clustering Web Search Frequency Time Series,
ICPR14(1544-1549)
IEEE DOI 1412
Data models BibRef

Chen, Y.[Yuansi], Mairal, J.[Julien], Harchaoui, Z.[Zaid],
Fast and Robust Archetypal Analysis for Representation Learning,
CVPR14(1478-1485)
IEEE DOI 1409
archetypal analysis; sparse coding BibRef

Kaufmann, D.[Dinu], Keller, S.[Sebastian], Roth, V.[Volker],
Copula Archetypal Analysis,
GCPR15(117-128).
Springer DOI 1511
BibRef

Prabhakaran, S.[Sandhya], Raman, S.[Sudhir], Vogt, J.E.[Julia E.], Roth, V.[Volker],
Automatic Model Selection in Archetype Analysis,
DAGM12(458-467).
Springer DOI 1209
Representative objects (text) BibRef

Bauckhage, C.[Christian], Thurau, C.[Christian],
Adapting Information Theoretic Clustering to Binary Images,
ICPR10(910-913).
IEEE DOI 1008
BibRef
Earlier:
Making Archetypal Analysis Practical,
DAGM09(272-281).
Springer DOI 0909
Represent as combination of extremal points. BibRef

Thurau, C.[Christian],
Nearest Archetype Hull Methods for Large-Scale Data Classification,
ICPR10(4040-4043).
IEEE DOI 1008
BibRef

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
K-Means Clustering .


Last update:Dec 7, 2019 at 17:16:29