A linear, discriminative, supervised technique for reducing feature vectors extracted from image data to a lower-dimensional representation is proposed. It is derived from classica...
— State of the art statistical timing analysis (STA) tools often yield less accurate results when timing variables become correlated due to global source of variations and path r...
Lizheng Zhang, Weijen Chen, Yuhen Hu, Charlie Chun...
Abstract. We focus on covariance criteria for finding a suitable subspace for regression in a reproducing kernel Hilbert space: kernel principal component analysis, kernel partial...
Luc Hoegaerts, Johan A. K. Suykens, Joos Vandewall...
We present a new method for spectral clustering with paired data based on kernel canonical correlation analysis, called correlational spectral clustering. Paired data are common i...
A convenient way of analysing Riemannian manifolds is to embed them in Euclidean spaces, with the embedding typically obtained by flattening the manifold via tangent spaces. This...