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Following the suggestions of a recent National Research Council report [NRC (National Research Council) (2006) Surface Temperature Reconstructions for the Last 2,000 Years (Natl Acad Press, Washington, DC).], we reconstruct surface temperature at hemispheric and global scale for much of the last 2,000 years using a greatly expanded set of proxy data for(More)
Global temperatures are known to have varied over the past 1500 years, but the spatial patterns have remained poorly defined. We used a global climate proxy network to reconstruct surface temperature patterns over this interval. The Medieval period is found to display warmth that matches or exceeds that of the past decade in some regions, but which falls(More)
The performance of image retrieval with SVM active learning is known to be poor when started with few labelled images only. In this paper, the problem is solved by incorporating the unlabelled images into the bootstrapping of the learning process. In this work, the initial SVM classifier is trained with the few labelled images and the unlabelled images(More)
In order to alleviate the problem of local convergence of the usual EM algorithm, a split-and-merge operation is introduced into the EM algorithm for Gaussian mixtures. The split-and-merge equations are 7rst presented theoretically. These equations show that the merge operation is a well-posed problem, whereas the split operation is an ill-posed problem(More)
The noncoding RNAs and protein related biomacromolecules interaction database (NPInter; http://bioinfo.ibp.ac.cn/NPInter or http://www.bioinfo.org.cn/NPInter) is a database that documents experimentally determined functional interactions between noncoding RNAs (ncRNAs) and protein related biomacromolecules (PRMs) (proteins, mRNAs or genomic DNAs). NPInter(More)
It has been of great interest to find sparse and/or nonnegative representations in computer vision literature. In this paper we propose a novel method to such a purpose and refer to it as nonnegative curds and whey (NNCW). The NNCW procedure consists of two stages. In the first stage we consider a set of sparse and nonnegative representations of a test(More)
Many emerging applications formulate nonpositive semidefinite similarity matrices, and hence cannot fit into the framework of kernel machines. A popular approach to this problem is to transform the spectrum of the similarity matrix so as to generate a positive semidefinite kernel matrix. In this paper, we present an analytical framework to explore four(More)
It is well known that the expression noise is lessened by natural selection for genes that are important for cell growth or are sensitive to dosage. In theory, expression noise can also be elevated by natural selection when noisy gene expression is advantageous. Here we analyze yeast genome-wide gene expression noise data and show that plasma-membrane(More)
The CUR matrix decomposition and the Nyström approximation are two important lowrank matrix approximation techniques. The Nyström method approximates a symmetric positive semidefinite matrix in terms of a small number of its columns, while CUR approximates an arbitrary data matrix by a small number of its columns and rows. Thus, CUR decomposition can be(More)