Titlebook: Neural Information Processing; 21st International C Chu Kiong Loo,Keem Siah Yap,Kaizhu Huang Conference proceedings 2014 Springer Internati

擔(dān)憂

A Kernel Method to Extract Common Features Based on Mutual Informationetween nonlinear mappings of the data. However, the kernel CCA tends to obtain the features that have only small information of original multivariates in spite of their high correlation, because it considers only statistics of the extracted features and the nonlinear mappings have high degree of fre

acquisition

flamboyant

性學(xué)院

Non-negative Matrix Factorization with Schatten p-norms Reguralizationlarization terms were previously added to the NMF objective function in order to produce sparser results and thus to obtain a more qualitative partition of data. We would like to propose the general framework for regularized NMF based on Schatten p-norms. Experimental results show the effectiveness

遍及

A New Energy Model for the Hidden Markov Random Fieldsood energy function of the Hidden Markov Random Fields model based on the Hidden Markov Model formalism. With this new energy model, we aim at (1) avoiding the use of a key parameter chosen empirically on which the results of the current models are heavily relying, (2) proposing an information rich

INCH

貪婪的人

A Computational Model of Anti-Bayesian Sensory Integration in the Size-Weight Illusionhe SWI refers to the fact that people judge the smaller of two equally weighted objects to heavier when lifted. Many aspects of human perceptual and motor behavior can be modeled with Bayesian statistics. However, the SWI cannot be explained on the basis of Bayesian integration, and the nervous syst

Valves

Unsupervised Dimensionality Reduction for Gaussian Mixture Modelodel (GMM), a famous model, has been widely used in various applications, e.g., clustering and classification. For high-dimensional data, previous research usually performs dimensionality reduction first, and then inputs the reduced features to other available models, e.g., GMM. In particular, there

緯線

Graph Kernels Exploiting Weisfeiler-Lehman Graph Isomorphism Test Extensionsing phase of the nodes based on test-specific information extracted from the graph, for example the set of neighbours of a node. We defined a novel relabelling and derived two kernels of the framework from it. The novel kernels are very fast to compute and achieve state-of-the-art results on five re

gnarled

Texture Analysis Based Automated Decision Support System for Classification of Skin Cancer Using SA-cal decision support system aimed to save lives, time and resources in the early diagnostic process. Segmentation, feature extraction, and lesion classification are the important steps in the proposed system. The system analyses the images to extract the affected area using a novel proposed segmenta