The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper combines an efficient reinforcement learning algorithm named Multisamples in Each Cell (MEC) with a building thermal comfort control problem. It implements the efficient exploration rule and makes high use of observed samples. A grid is utilized to partition the continuous state into cells that are used to store samples. A near-upper Q function is obtained based on the samples in each cell...
We propose an optimization method for belief propagation. First we mathematically show that the belief propagation algorithm can be optimized by imposing a reasonable restriction on the conditional probability tables in a Bayesian network. Then we demonstrate the efficiency of the proposed algorithm with experiments. Compared to the previously derived approximate algorithm, the proposed algorithm...
A new sparse kernel density estimator is introduced based on the minimum integrated square error criterion combining local component analysis for the finite mixture model. We start with a Parzen window estimator which has the Gaussian kernels with a common covariance matrix, the local component analysis is initially applied to find the covariance matrix using expectation maximization algorithm. Since...
Several clustering algorithms have been developed and applied to a great variety of problems in different fields. However, some of these algorithms have limitations. Bio-inspired algorithms have been applied to clustering problems aiming to overcome some of these limitations. In this paper, we apply the Coral Reefs Optimization (CRO) algorithm to clustering problems. The CRO algorithm has been originally...
The automatic design of control systems for multi-robot teams that operate in real time is not affordable with traditional evolutionary algorithms mainly due to the huge computational requirements they imply. Embodied Evolution (EE) is an evolutionary paradigm that aims to address this problem through the embodiment of the individuals that make up the population in the physical robots. The interest...
This paper introduces a new framework for author recommending using Multi-Layer Self-Organizing Map (ML-SOM). Concretely, an author is modeled by a tree-structured representation, and an MLSOM-based system is used as an efficient solution to the content-based author recommending problem. The tree-structured representation formulates author features in a hierarchy of author biography, written books...
In many real-world applications, it is often the case that the class distribution of example is imbalanced and the costs of misclassification are different. In such circumstances, not classification accuracy but misclassification cost minimization is the primary goal leading to the development of the class-imbalanced cost-sensitive learning. Under-sampling is one of the most important methods in dealing...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.