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Clustering in high-dimensional spaces is a recurrent problem in many domains, for example in object recognition. High-dimensional data usually live in different low-dimensional subspaces hidden in the original space. This paper presents a clustering approach which estimates the specific subspace and the intrinsic dimension of each class. Our approach adapts(More)
Sliced Inverse Regression (SIR) is an effective method for dimension reduction in high-dimensional regression problems. The original method, however, requires the inversion of the predictors covariance matrix. In case of collinearity between these predictors or small sample sizes compared to the dimension, the inversion is not possible and a regularization(More)
This paper is concerned with the estimation of a local measure of intrinsic dimensionality (ID) recently proposed by Houle. The local model can be regarded as an extension of Karger and Ruhl's expansion dimension to a statistical setting in which the distribution of distances to a query point is modeled in terms of a continuous random variable. This form of(More)
Stem cell-based therapy has been proposed as a potential means of treatment for a variety of brain disorders. Because ethical and technical issues have so far limited the clinical translation of research using embryonic/fetal cells and neural tissue, respectively, the search for alternative sources of therapeutic stem cells remains ongoing. Here, we report(More)
The olfactory mucosa, located in the nasal cavity, is in charge of detecting odours. It is also the only nervous tissue that is exposed to the external environment and easily accessible in every living individual. As a result, this tissue is unique for anyone aiming to identify molecular anomalies in the pathological brain or isolate adult stem cells for(More)
The frontal cortex is a brain structure that plays an important role in cognition and is known to be affected in Alzheimer's disease (AD) in humans. Over the past years, transgenic mouse models have been generated to recapitulate the main features of this disease, including cognitive impairments. This study investigates frontal cortex dependent learning(More)
In the supervised classification framework, human supervision is required for labeling a set of learning data which are then used for building the classifier. However, in many applications, human supervision is either imprecise, difficult or expensive. In this paper, the problem of learning a supervised multi-class classifier from data with uncertain labels(More)
In the context of network traffic analysis, we address the problem of estimating the tail index of flow (or more generally of any group) size distribution from the observation of a sampled population of packets (individuals). We give an exhaustive bibliography of the existing methods and show the relations between them. The main contribution of this work is(More)
HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt età la diffusion(More)