We develop exact and approximate algorithms for computing optimal separators and measuring the extent to which two point sets in d-dimensional space are separated, with respect to different classes of separators and various extent measures. This class of geometric problems generalizes two widely studied problem families, namely separability and the computation of statistical estimators.
We consider a fundamental problem in unsupervised learning called subspace recovery: given a collect...
In this paper, we study the linear separability problem for stochastic geometric objects under the w...
International audienceWe present a near linear algorithm for determining the linear separability of ...
AbstractGiven linearly inseparable sets R of red points and B of blue points, we consider several me...
We consider the problem of removing c points from a set S of n points so that the remaining point se...
AbstractWe study the problem of finding an outlier-free subset of a set of points (or a probability ...
One recently proposed criterion to separate two datasets in dis-criminant analysis, is to use a hype...
We describe an O(nd) time algorithm for computing the exact probability that two d-dimensional proba...
An imprecise point is a point p with an associated imprecision region Ip indicating the set of possi...
Consider the following fundamental problem: given two sets R and G of objects positioned in d-dimens...
We prove new theorems which describe a necessary and sufficient condition for linear (strong and non...
AbstractWe introduce the notion of the width bounded geometric separator and develop the techniques ...
We consider the problem of removing c points from a set S of n points so that the remaining point se...
We consider the problem of removing c points from a set S of n points so that the remaining point se...
Separators in graphs are instrumental in the design of algorithms, having proven to be the key techn...
We consider a fundamental problem in unsupervised learning called subspace recovery: given a collect...
In this paper, we study the linear separability problem for stochastic geometric objects under the w...
International audienceWe present a near linear algorithm for determining the linear separability of ...
AbstractGiven linearly inseparable sets R of red points and B of blue points, we consider several me...
We consider the problem of removing c points from a set S of n points so that the remaining point se...
AbstractWe study the problem of finding an outlier-free subset of a set of points (or a probability ...
One recently proposed criterion to separate two datasets in dis-criminant analysis, is to use a hype...
We describe an O(nd) time algorithm for computing the exact probability that two d-dimensional proba...
An imprecise point is a point p with an associated imprecision region Ip indicating the set of possi...
Consider the following fundamental problem: given two sets R and G of objects positioned in d-dimens...
We prove new theorems which describe a necessary and sufficient condition for linear (strong and non...
AbstractWe introduce the notion of the width bounded geometric separator and develop the techniques ...
We consider the problem of removing c points from a set S of n points so that the remaining point se...
We consider the problem of removing c points from a set S of n points so that the remaining point se...
Separators in graphs are instrumental in the design of algorithms, having proven to be the key techn...
We consider a fundamental problem in unsupervised learning called subspace recovery: given a collect...
In this paper, we study the linear separability problem for stochastic geometric objects under the w...
International audienceWe present a near linear algorithm for determining the linear separability of ...
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