A new approach to the Text Categorization problem is here presented. It is called Gaussian Weighting and it is a supervised learning algorithm that, during the training phase, est...
We propose a network model of spiking neurons, without preimposed topology and driven by STDP (Spike-Time-Dependent Plasticity), a temporal Hebbian unsupervised learning mode, biol...
Prediction is an important task in robot motor control where it is used to gain feedback for a controller. With such a self-generated feedback, which is available before sensor rea...
Abstract— This paper presents an approach to create topological maps from geometric maps obtained with a mobile robot in an indoor-environment using range data. Our approach util...
In this paper we propose a weakly supervised learning algorithm for appearance models based on the minimum description length (MDL) principle. From a set of training images or volu...
Georg Langs, Rene Donner, Philipp Peloschek, Horst...
AIRS is an immune-inspired supervised learning algorithm that has been shown to perform competitively on some common datasets. Previous analysis of the algorithm consists almost ex...
Automated detection of the first document reporting each new event in temporally-sequenced streams of documents is an open challenge. In this paper we propose a new approach which...
Yiming Yang, Jian Zhang, Jaime G. Carbonell, Chun ...
Given a set of images of scenes containing different object categories (e.g. grass, roads) our objective is to discover these objects in each image, and to use this object occurre...
Anna Bosch, Arnau Oliver, Robert Marti, Xavier Mu&...