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Business Strategy and the Environment, EarlyView.ABSTRACT Despite global commitments under the Paris Agreement, empirical evidence on the involvement of the land‐based private sector of emerging economies in carbon trading remains limited. The study analyses how behavioural factors and institutional complexities influence the involvement of the land‐based private sector in carbon trading in Indonesia.
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Neighborhood linear discriminant analysis
Pattern Recognition, 2022Abstract Linear Discriminant Analysis (LDA) assumes that all samples from the same class are independently and identically distributed (i.i.d.). LDA may fail in the cases where the assumption does not hold. Particularly when a class contains several clusters (or subclasses), LDA cannot correctly depict the internal structure as the scatter matrices ...
Fa Zhu, Junbin Gao, Jian Yang
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Regularized orthogonal linear discriminant analysis [PDF]
Pattern Recognition, 2012 In this paper the regularized orthogonal linear discriminant analysis (ROLDA) is studied. The major issue of the regularized linear discriminant analysis is to choose an appropriate regularization parameter.
Wai-Ki Ching, Delin Chu, Li-Zhi Liao
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Linear Discriminant Analysis for Signatures
IEEE Transactions on Neural Networks, 2010We propose signature linear discriminant analysis (signature-LDA) as an extension of LDA that can be applied to signatures, which are known to be more informative representations of local image features than vector representations, such as visual word histograms.
S. Huh, D. Lee
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Network linear discriminant analysis
Computational Statistics & Data Analysis, 2018zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Wei Cai +4 more
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Nonstationary linear discriminant analysis
2017 51st Asilomar Conference on Signals, Systems, and Computers, 2017Changes in population distributions over time are common in many applications. However, the vast majority of statistical learning theory takes place under the assumption that all points in the training data are identically distributed (and independent), that is, non-stationarity of the data is disregarded. In this paper, a version of the classic Linear
Shuilian Xie +3 more
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Distributed linear discriminant analysis
2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2011Linear discriminant analysis (LDA) is a widely used feature extraction method for classification. We introduce distributed implementations of different versions of LDA, suitable for many real applications. Classical eigen-formulation, iterative optimization of the subspace, and regularized LDA can be asymptotically approximated by all the nodes through
Sergio Valcarcel Macua +2 more
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Laplacian linear discriminant analysis
Pattern Recognition, 2006zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Hong Tang, Tao Fang, Pengfei Shi
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Linear boundary discriminant analysis
Pattern Recognition, 2010zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jin Hee Na +2 more
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Linear discriminant analysis for speechreading
1998 IEEE Second Workshop on Multimedia Signal Processing (Cat. No.98EX175), 2002This paper investigates the use of Fisher-Rao (1965) linear discriminant analysis (LDA) as a means of visual feature extraction for hidden Markov model based automatic speechreading. For every video frame, a three-dimensional region of interest containing the speaker's mouth over a sequence of adjacent frames is lexicographically arranged into a data ...
Gerasimos Potamianos, Hans Peter Graf
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