kernel canonical correlation analysis (KCCA) is a recently addressed supervised machine learning methods, which shows to be a powerful approach of extracting nonlinear features for...
Given a sample covariance matrix, we examine the problem of maximizing the variance explained by a linear combination of the input variables while constraining the number of nonze...
Alexandre d'Aspremont, Francis R. Bach, Laurent El...
The ability to find tables and extract information from them is a necessary component of many information retrieval tasks. Documents often contain tables in order to communicate d...
Abstract. This paper presents a multi-agent approach to gene expression analysis and illustrates the working steps using real dataset produced from a microarray experiment. The ana...
H. C. Lam, M. Vazquez, B. Juneja, Scott C. Fahrenk...
The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...