CVPR
2012
IEEE
11 years 7 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
12 years 12 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 2 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 4 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
13 years 5 months 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
13 years 5 months 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
13 years 6 months 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
13 years 8 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
13 years 9 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
13 years 9 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...