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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)
Several risk measures have been proposed in the literature. In this paper, we focus on the estimation of the Conditional Tail Expectation (CTE). Its asymptotic normality has been first established in the literature under the classical assumption that the second moment of the loss variable is finite, this condition being very restrictive in practical(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)
We consider the high order moments estimator of the frontier of a random pair, intro-high order moments. In the present paper, we show that this estimator is strongly uniformly consistent on compact sets and its rate of convergence is given when the conditional cumulative distribution function belongs to the Hall class of distribution functions.
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)