We introduce the notion of relevant information loss for the purpose of casting the signal enhancement problem in information-theoretic terms. We show that many algorithms from machine learning can be reformulated using relevant information loss, which allows their application to the aforementioned problem. As a particular example we analyze principle component analysis for dimensionality reduc...

Many machine learning applications require classi ers that minimize an asymmetric loss function rather than the raw misclassi cation rate. We study methods for modifying C4.5 to incorporate arbitrary loss matrices. One way to incorporate loss information into C4.5 is to manipulate the weights assigned to the examples from di erent classes. For 2-class problems, this works for any loss matrix, b...

The one-bit quantization can be implemented by one single comparator, which operates at low power and a high rate. Hence one-bit compressive sensing (1bit-CS) becomes very attractive in signal processing. When the measurements are corrupted by noise during signal acquisition and transmission, 1bit-CS is usually modeled as minimizing a loss function with a sparsity constraint. The existing loss ...

The semi-supervised learning usually only predict labels for unlabeled data appearing in training data, and cannot effectively predict labels for testing data never appearing in training set. To handle this outof-sample problem, many inductive methods make a constraint such that the predicted label matrix should be exactly equal to a linear model. In practice, this constraint is too rigid to ca...

Distributed Generation is the generation of electricity from many small energy sources and is located closer to the user, or customer. This paper presents analytical method to determine the optimal location to place a distributed generation in radial feeder model to minimize the real power loss of the system. The analytical expression and the methodology are based on the power flow method. The ...

An efficient distribution network must be able to supply power with good voltage profile. The main objective of the proposed work is to allocate losses of the unbalanced distribution network by the firefly algorithm in regulated and deregulated environments before and after loss minimization. Reconfiguration is one of the methods for loss reduction of unbalanced distribution network. Further, o...