In this paper we consider the problem of minimizing a convex differentiable function subject to sparsity constraints. Such constraints are non-convex and the resulting optimization problem is known to be hard to solve. We propose a novel generalization of this problem and demonstrate that it is equivalent to the original sparsity-constrained problem if a certain weighting term is sufficiently l...

We describe a sequential universal data compression procedure for binary tree sources that performs the " double mixture. " Using a context tree, this method weights in an efficient recursive way the coding distributions corresponding to all bounded memory tree sources, and achieves a desirable coding distribution for tree sources with an unknown model and unknown parameters. Computational and ...

PURPOSE Adaptive radiation therapy (ART) can reduce normal tissue toxicity and/or improve tumor control through treatment adaptations based on the current patient anatomy. Developing an efficient re-planning algorithm is an important step for ART. For the re-planning process, manual trial-and-error approach to fine-tune planning parameters is a time- consuming and resource-requiring task. Howev...

DNA sequencing enables the discovery of new genes in high-throughput, low-cost experiments. Conversely, gene function is determined by low-throughput, high-cost experiments. This inverse relationship for these two types of data is a major impediment in meeting one of the major scientific challenges of our time—the understanding of genomes. This mismatch in throughput is illustrated by consideri...

An approach to determining the optimal cell number of manufacturing cell formation is presented. Firstly, the difference of weighting exponent, cluster center and metrics how to have an impact upon the clustering results and membership function are studied. Secondly, a method to determine the optimal m value is given. Two-order partial derivative of the objective function for FCM is calculated,...

In this paper, a nest of iterative techniques is proposed for the minimax design of quadrature mirror filter (QMF) banks. The method can be generalized such that multidimensional QMF banks can be designed by the proposed algorithm. For a given weighting function, an iterative method is used to minimize the objective error function in the inner iterations. To further reduce the peak error of ove...

recently, tuning the weights of the rules in fuzzy rule-base classification systems is researched in order to improve the accuracy of classification. in this paper, a margin-based optimization model, inspired by support vector machine classifiers, is proposed to compute these fuzzy rule weights. this approach not only  considers both accuracy and generalization criteria in a single objective fu...

Feature weighting algorithms try to solve a problem of great importance nowadays in machine learning: The search of a relevance measure for the features of a given domain. This relevance is primarily used for feature selection as feature weighting can be seen as a generalization of it, but it is also useful to better understand a problem’s domain or to guide an inductor in its learning process....