Classification on Stiefel and Grassmann Manifolds via Maximum Likelihood Estimation of Matrix Distributions

Muhammad Ali

doi:10.1109/IJCNN.2016.7727683

Classification on Stiefel and Grassmann Manifolds via Maximum Likelihood Estimation of Matrix Distributions

Muhammad Ali

Research output: Book chapter/Published conference paper › Conference paper › peer-review

1 Citation (Scopus)

Abstract

Classification via manifold valued data by using matrix-Fisher and Matrix-Bingham Distribution. The model is based on matrix based normalising constant.

Original language	English
Title of host publication	Proceedings of the 2016 International Joint Conference on Neural Networks (IJCNN)
Place of Publication	United States
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	3751-3757
Number of pages	7
ISBN (Electronic)	9781509006199
DOIs	https://doi.org/10.1109/IJCNN.2016.7727683
Publication status	Published - 2016
Event	IEEE International Joint Conference on Neural Networks: IJCNN 2016 - Vancouver Convention Centre, Vancouver, Canada Duration: 24 Jul 2016 → 29 Jul 2016 https://web.archive.org/web/20160319082904/http://www.wcci2016.org:80/ (Conference website)

Conference

Conference	IEEE International Joint Conference on Neural Networks
Country/Territory	Canada
City	Vancouver
Period	24/07/16 → 29/07/16
Other	On behalf of the organizing committee, it is our great pleasure to invite you to the bi-annual IEEE World Congress on Computational Intelligence (IEEE WCCI) which will be held in the magnificent city of Vancouver, Canada, 24-29 July 2016. Financially sponsored by the IEEE Computational Intelligence Society (CIS), IEEE WCCI 2016 will host three conferences: The 2016 International Joint Conference on Neural Networks (IJCNN 2016), the 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2016), and the 2016 IEEE Congress on Evolutionary Computation (IEEE CEC 2016) under one roof.
Internet address	https://web.archive.org/web/20160319082904/http://www.wcci2016.org:80/ (Conference website)

Access to Document

10.1109/IJCNN.2016.7727683

Cite this

@inproceedings{670e3635af554b7f907dc7cb589bb05c,

title = "Classification on Stiefel and Grassmann Manifolds via Maximum Likelihood Estimation of Matrix Distributions",

abstract = "Classification via manifold valued data by using matrix-Fisher and Matrix-Bingham Distribution. The model is based on matrix based normalising constant.",

keywords = "Matrix manifolds, Hyper-geometric functions Maximum Likelihood Estimation (MLE), Classification.",

author = "Muhammad Ali",

note = "Imported on 03 May 2017 - DigiTool details were: publisher = Canada: IEEE, 2016. Event dates (773o) = 24-29 July 2016; Parent title (773t) = IEEE International Joint Conference on Neural Networks.; IEEE International Joint Conference on Neural Networks : IJCNN 2016 ; Conference date: 24-07-2016 Through 29-07-2016",

year = "2016",

doi = "10.1109/IJCNN.2016.7727683",

language = "English",

pages = "3751--3757",

booktitle = "Proceedings of the 2016 International Joint Conference on Neural Networks (IJCNN)",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States",

url = "https://web.archive.org/web/20160319082904/http://www.wcci2016.org:80/",

}

Ali, M 2016, Classification on Stiefel and Grassmann Manifolds via Maximum Likelihood Estimation of Matrix Distributions. in Proceedings of the 2016 International Joint Conference on Neural Networks (IJCNN). IEEE, Institute of Electrical and Electronics Engineers, United States, pp. 3751-3757, IEEE International Joint Conference on Neural Networks, Vancouver, British Columbia, Canada, 24/07/16. https://doi.org/10.1109/IJCNN.2016.7727683

Classification on Stiefel and Grassmann Manifolds via Maximum Likelihood Estimation of Matrix Distributions. / Ali, Muhammad.
Proceedings of the 2016 International Joint Conference on Neural Networks (IJCNN). United States: IEEE, Institute of Electrical and Electronics Engineers, 2016. p. 3751-3757.

Research output: Book chapter/Published conference paper › Conference paper › peer-review

TY - GEN

T1 - Classification on Stiefel and Grassmann Manifolds via Maximum Likelihood Estimation of Matrix Distributions

AU - Ali, Muhammad

N1 - Imported on 03 May 2017 - DigiTool details were: publisher = Canada: IEEE, 2016. Event dates (773o) = 24-29 July 2016; Parent title (773t) = IEEE International Joint Conference on Neural Networks.

PY - 2016

Y1 - 2016

N2 - Classification via manifold valued data by using matrix-Fisher and Matrix-Bingham Distribution. The model is based on matrix based normalising constant.

AB - Classification via manifold valued data by using matrix-Fisher and Matrix-Bingham Distribution. The model is based on matrix based normalising constant.

KW - Matrix manifolds, Hyper-geometric functions Maximum Likelihood Estimation (MLE), Classification.

U2 - 10.1109/IJCNN.2016.7727683

DO - 10.1109/IJCNN.2016.7727683

M3 - Conference paper

SP - 3751

EP - 3757

BT - Proceedings of the 2016 International Joint Conference on Neural Networks (IJCNN)

PB - IEEE, Institute of Electrical and Electronics Engineers

CY - United States

T2 - IEEE International Joint Conference on Neural Networks

Y2 - 24 July 2016 through 29 July 2016

ER -

Classification on Stiefel and Grassmann Manifolds via Maximum Likelihood Estimation of Matrix Distributions

Abstract

Conference

Access to Document

Fingerprint

Cite this