Abstract. Embedding high-dimensional patterns in low-dimensional latent spaces is a challenging task. In this paper, we introduce re-sampling strategies to leave local optima in the data space reconstruction error (DSRE) minimization process of unsupervised kernel regression (UKR). For this sake, we concentrate on a hybrid UKR variant that combines iterative solution construction with gradient ...

Local linear regression performs very well in many low-dimensional forecasting problems. In high-dimensional spaces, its performance typically decays due to the well-known "curse-of-dimensionality". A possible way to approach this problem is by varying the "shape" of the weighting kernel. In this work we suggest a new, data-driven method to estimating the optimal kernel shape. Experiments using...

In addition to being invariant to image rotation and translation, histograms have the advantage of being easy to compute. These advantages make histograms very popular in computer vision. However, without data quantization to reduce size, histograms are generally not suitable for realtime applications. Moreover, they are sensitive to quantization errors and lack any spatial information. This pa...

The consistency of the local kernel density estimator is proved. This nonparametric estimator is distinguished by its use of scaling matrices which are random and which may vary for each sample point. Its applications include adaptive construction of importance sampling functions.

Almost all types of computer game require some form of steering strategy to allow the AI agents to move around in the environment. Indeed such methods must form a solid base on which to build the remainder of the game AI. Some of the commonly used methods which can be categorised as short range steering (local steering) or long range (predominantly path finding) are reviewed and compared, with ...

Almost all types of computer game require some form of steering strategy to allow the AI agents to move around in the environment. Indeed such methods must form a solid base on which to build the remainder of the game AI. Some of the commonly used methods which can be categorised as short range steering (local steering) or long range (predominantly path finding) are reviewed and compared, with ...

In this paper a novel framework for brain classification is proposed in the context of mental health research. A learning by example method is introduced by combining local measurements with non linear Support Vector Machine. Instead of considering a voxel-by-voxel comparison between patients and controls, we focus on landmark points which are characterized by local region descriptors, namely S...