One of the main challenges of strategic management is implementing the strategies. Designing the strategy map in Balanced Scorecard framework to determine the causality between strategic objectives is one of the most important issues in implementing the strategies. In designing the strategy map with intuition and judgment, the link between strategic objectives is not clear and it is not obvious...

We develop a novel method for zero shot learning (ZSL) based on test-time adaptation of similarity functions learned using training data. Existing methods exclusively employ source-domain side information for recognizing unseen classes during test time. We show that for batch-mode applications, accuracy can be significantly improved by adapting these predictors to the observed test-time target-...

The analysis of a speech segment is conventionally performed through linear prediction and the subsequent minimisation of a data error term in the least squares sense. The parameters derived as such maximise the likelihood of the data. In a learning problem, the addition of penalty terms, or regularisers, to the data term facilitates the estimation of the Maximum a Posteriori , or MAP, paramete...

Our route choices depend on our own mental map of the city. This assumption, brought from the areas of spatial cognition and cognitive mapping, establishes a distorted graph as the cognitive model that represents our trips. The task of trajectory prediction consists of determining, when a driver is making a trip, which path will be chosen. Our approach consists of transforming the map according...

In this paper, we compare the inference capabilities of three different types of Fuzzy Cognitive Maps. A Fuzzy Cognitive Map is a Recurrent Artificial Neural Network that creates models as collections of concepts/neurons and the various causal relations that exist between these concepts/neurons. The three different types of Fuzzy Cognitive Maps that we study are the Binary, the Trivalent and th...

We applied an Iteratively Reweighted Least Squares (IRLS) approach to create a map of the Sea of Galilee. We use a bank of Prediction Error Filters (PEFs) as a residual whitener to reduce the acquisition footprint and map artifacts caused by non-Gaussian noise in the data.

This study attempts to show how a Kohonen map can be used to improve the temporal stability of the accuracy of a financial failure model. Most models lose a significant part of their ability to generalize when data used for estimation and prediction purposes are collected over different time periods. As their lifespan is fairly short, it becomes a real problem if a model is still in use when re...

This paper presents a prediction of the millimeterwave multipath propagation characteristics in the typical urban environment. To analyze the propagation in an outdoor environment, the three dimensional model based on the geometrical optics and the uniform geometrical theory of diffraction is employed. Prediction by the three dimensional ray tracing method needs a detailed map, which records lo...

This work presents an approach to learn path planning for robot social navigation by demonstration. We make use of Fully Convolutional Neural Networks (FCNs) to learn from expert’s path demonstrations a map that marks a feasible path to the goal as a classification problem. The use of FCNs allows us to overcome the problem of manually designing/identifying the cost-map and relevant features for...

This paper describes how formant frequencies of voiced and unvoiced speech can be predicted from mel-frequency cepstral coefficients (MFCC) vectors using maximum a posteriori (MAP) estimation within a hidden Markov model (HMM) framework. Gaussian mixture models (GMMs) are used to model the local joint density of MFCCs and formant frequencies. More localised prediction is achieved by modelling s...