In this article, we explore the concept of minimization of information loss (MIL) as a a target for neural network learning. We relate MIL to supervised and unsupervised learning procedures such as the Bayesian maximum a-posteriori (MAP) discriminator, minimization of distortion measures such as mean squared error (MSE) and cross-entropy (CE), and principal component analysis (PCA). To deal wit...

In practical analysis, domain knowledge about analysis target has often been accumulated, although, typically, such knowledge has been discarded in the statistical analysis stage, and the statistical tool has been applied as a black box. In this paper, we introduce sign constraints that are a handy and simple representation for non-experts in generic learning problems. We have developed two new...

We propose a general method for reranker construction which targets choosing the candidate with the least expected loss, rather than the most probable candidate. Different approaches to expected loss approximation are considered, including estimating from the probabilistic model used to generate the candidates, estimating from a discriminative model trained to rerank the candidates, and learnin...

risk management is one of the most important aspects of project management that identifies, assesses and responds to project risks. although many papers have been published in project risk response, presented tools and methods are poor. hence, in this paper, we present an optimization model to respond project risk that seeks to optimize two key criteria of project: cost and time. the proposed m...

We give improved constants for data dependent and variance sensitive confidence bounds, called empirical Bernstein bounds, and extend these inequalities to hold uniformly over classes of functions whose growth function is polynomial in the sample size n. The bounds lead us to consider sample variance penalization, a novel learning method which takes into account the empirical variance of the lo...

With the development of industry, population growth, and suburbanization, load demand is constantly increasing from year to year. Overload has greatly strained distribution network (DN), resulting in increased power losses due high-power flow. Therefore, it becomes very important minimize at DN maximize efficiency companies. Network reconfiguration one effective methods companies use DN. This p...