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A conventional weight in an artificial neural network has a single trainable real value and produces a linear relationship between the weight input and the weight output. A real synaptic cleft is also trainable but provides a more complex relationship. It is obvious to wonder if adding extra complexity to the conventional weight response would lead to more capable networks. This work describes a weight...
Accurate forecasting of solar power is needed for the successful integration of solar energy into the electricity grid. In this paper we consider the task of predicting the half-hourly solar photovoltaic power for the next day from previous solar power and weather data. We propose and evaluate several clustering based methods, that group the days based on the weather characteristics and then build...
We show that simple linear classification of pairwise products of convolutional features achieves near state-of-the-art performance on some standard labelled image databases. Specifically, we found test classification error rates on the MNIST handwritten digits image database of under 0.5%, and achieved under 19% and under 44% error rates on the CIFAR-10 and CIFAR-100 RGB image databases. Since the...
With the emergence of data streaming applications that produce large data in motion, anomaly detection in non-stationary environments has become a major research focus. Unknown and unstable behaviour of data over time, limits the application of traditional anomaly detection methods that have been designed for stationary data. Moreover, basic assumptions of many existing works in the adaptive anomaly...
Learning now occurs in various manners in social networks, utilizing practice communities and learning networks. In this context, students are interested in exploring learning activities of other students without having to read through large quantities of textual content. Students tend to be interested in finding information concerning their majors, contents of their subjects and their co-learners...
In this paper, we employ graph embeddings for classification tasks. To do this, we explore the relationship between kernel matrices, spaces of inner products and statistical inference by viewing the embedding vectors for the nodes in the graph as a field on a Riemannian manifold. This leads to a setting where the inference process may be cast as a Maximum a Posteriori (MAP) estimation over a Gibbs...
Online reviews nowadays are an important source of information for consumers to evaluate online services and products before deciding which product and which provider to choose. Therefore, online reviews have significant power to influence consumers' purchase decisions. Being aware of this, an increasing number of companies have organized spammer review campaigns, in order to promote their products...
The multichannel nature of EEG and EMG data poses a big challenge to the development of automatic EEG/EMG analysis and classification systems. Due to the “curse of dimensionality” problem, the analysis and classification of several channels may not lead to the desired performance. Accordingly, a number of algorithms have been proposed to identify small “static” subsets of channels that are capable...
Deep learning has become increasingly popular in both academic and industrial areas in the past years. Various domains including pattern recognition, computer vision, and natural language processing have witnessed the great power of deep networks. However, current studies on deep learning mainly focus on data sets with balanced class labels, while its performance on imbalanced data is not well examined...
We consider the task of forecasting the electricity power generated by a photovoltaic solar system, for the next day at half-hourly intervals. The forecasts are based on previous power output and weather data, and weather prediction for the next day. We present a new approach that forecasts all the power outputs for the next day simultaneously. It builds separate prediction models for different types...
Pluralistic ignorance (PI) is a common phenomenon, observed in many social settings. It occurs when the majority of a group become non-believer conformist, but mistakenly perceive others to be true conformist. PI takes many forms and leads to a wide variety of social problems, from binge drinking to repressive political regimes and ideologies. Although discussed extensively in the literature, the...
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