… the correlation relation of different modalities. In this paper, we introduce a shared feature
learning method for emotion recognition using En-… the correlation relation of intra-class and …

… loss term of the source domain: We expect to reduce the intra-class variation of the source
domain. It is important note that we can also leverage the different penalty coefficients \( {{n_{s…

… discriminative deep canonical correlation analysis (D2CCA), for classifying given observations
into multiple categories. The learning … -class variations and minimizes the within-class …

… Cipolla, “Discriminative learning and recognition of image set classes using canonical
correlations,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 29, no. 6, pp. …

… Denote C X i X j w and C X i X j b are the intra-class and inter-class correlation matrices of
feature sets X i and X j respectively, which are defined as follows:(6) C X i X j w = X i MX j T , C …

… class-wise discriminative CCA that performed class correlation via a predefined discriminant
… deals with the existing discriminative CCA models by 1) the global discriminative CCA [34], […

… 2D feature visualization of (a) the original features, (b) the features learned using our
ODFDL method. Here, we randomly chosen 8 image sets with one set per class from the YTC …

… learning, but the intrinsic discriminative representation is also explored by maximizing the
within-class correlation and minimizing the betweenclass … discriminative canonical correlation …

… correlation across different data sets. As a typical representation for linear correlation analysis,
canonical correlation … of the within-class matrix are utilized jointly to construct a complete …

… Presently, there are many effective algorithms for multifeature learning 1 – 5 to extract the
discriminant features and reduce the … (4), we show 12 images of two classes in RCLD. …