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A retrospective study was performed in patients diagnosed with primary lung cancer, and admitted to the Instituto Nacional de Enfermedades Respiratorias between 1984 to 1992. One thousand and nineteen patients were studied, 636 males and 383 females. We found a higher incidence in the group among 61-70 years of age in both sexes. The highest percentage of(More)
We study the problem of learning a sparse linear regression vector under additional conditions on the structure of its sparsity pattern. We present a family of convex penalty functions, which encode this prior knowledge by means of a set of constraints on the absolute values of the regression coefficients. This family subsumes the ℓ 1 norm and is flexible(More)
We study a generalized framework for structured sparsity. It extends the well known methods of Lasso and Group Lasso by incorporating additional constraints on the variables as part of a convex optimization problem. This framework provides a straightforward way of favouring prescribed sparsity patterns, such as orderings, contiguous regions and overlapping(More)
INTRODUCTION Mesoamerican nephropathy, also known as chronic kidney disease of unknown etiology, is widespread in Pacific coastal Central America. The cause of the epidemic is unknown, but the disease may be linked to multiple factors, including diet as well as environmental and occupational exposures. As many as 50% of men in some communities have(More)
Environmental monitoring is a key concern in underground mines, such as part of the copper mine of Codelco-Chile's Andina Division, in the central part of the country. The concentration of dust is important due to its negative effect in workers health. Regrettably, sensors for this parameter are costly and therefore implementing a full scale monitoring(More)
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