CVPR
2012
IEEE
12 years 1 months ago
2012
IEEE
We propose an energy-based framework for approximating surfaces from a cloud of point measurements corrupted by noise and outliers. Our energy assigns a tangent plane to each (noi...
CVPR
2011
IEEE
13 years 6 months ago
2011
IEEE
We consider the problem of fitting one or more subspaces to a collection of data points drawn from the subspaces and corrupted by noise/outliers. We pose this problem as a rank m...
NAACL
2010
13 years 8 months ago
2010
We show how the Barzilay and Lapata entitybased coherence algorithm (2008) can be applied to a new, noisy data domain
TIP
1998
13 years 10 months ago
1998
Abstract—Diffusions are useful for image processing and computer vision because they provide a convenient way of smoothing noisy data, analyzing images at multiple scales, and en...
VISAPP
2007
14 years 1 days ago
2007
In this paper, we address the problem of robustly recovering several instances of a curve model from a single noisy data set with outliers. Using M-estimators revisited in a Lagran...
KDID
2004
14 years 8 days ago
2004
We are designing new data mining techniques on boolean contexts to identify a priori interesting bi-sets (i.e., sets of objects or transactions associated to sets of attributes or ...
ESA
2008
Springer
14 years 19 days ago
2008
Springer
Metric Labeling problems have been introduced as a model for understanding noisy data with pair-wise relations between the data points. One application of labeling problems with pa...
ALT
1998
Springer
14 years 3 months ago
1998
Springer
An index for an r.e. class of languages (by definition) generates a sequence of grammars defining the class. An index for an indexed family of recursive languages (by definition) ...
CAIP
2001
Springer
14 years 3 months ago
2001
Springer
In this paper, using hypergraph theory, we introduce an image model called Adaptive Image Neighborhood Hypergraph (AINH). From this model we propose a combinatorial definition of ...
DAWAK
2009
Springer
14 years 3 months ago
2009
Springer
A process, based on argumentation theory, is described for classifying very noisy data. More specifically a process founded on a concept called “arguing from experience” is des...