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ICCV
2003
IEEE
15 years 28 days ago
Learning How to Inpaint from Global Image Statistics
Inpainting is the problem of filling-in holes in images. Considerable progress has been made by techniques that use the immediate boundary of the hole and some prior information o...
Anat Levin, Assaf Zomet, Yair Weiss
CVPR
2012
IEEE
12 years 1 months ago
Large scale metric learning from equivalence constraints
In this paper, we raise important issues on scalability and the required degree of supervision of existing Mahalanobis metric learning methods. Often rather tedious optimization p...
Martin Köstinger, Martin Hirzer, Paul Wohlhar...
ITS
2000
Springer
159views Multimedia» more  ITS 2000»
14 years 2 months ago
Can We Learn from ITSs?
With the rise of VR, the internet, and mobile technologies and the shifts in educational focus from teaching to learning and from solitary to collaborative work, it's easy (bu...
Benedict du Boulay
PODS
2006
ACM
134views Database» more  PODS 2006»
14 years 11 months ago
Approximate quantiles and the order of the stream
Recently, there has been an increased focus on modeling uncertainty by distributions. Suppose we wish to compute a function of a stream whose elements are samples drawn independen...
Sudipto Guha, Andrew McGregor
COLT
2005
Springer
14 years 4 months ago
A PAC-Style Model for Learning from Labeled and Unlabeled Data
Abstract. There has been growing interest in practice in using unlabeled data together with labeled data in machine learning, and a number of different approaches have been develo...
Maria-Florina Balcan, Avrim Blum