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ICCV
2011
IEEE
13 years 10 months ago
From Learning Models of Natural Image Patches to Whole Image Restoration
Learning good image priors is of utmost importance for the study of vision, computer vision and image processing applications. Learning priors and optimizing over whole images can...
Daniel Zoran, Yair Weiss
WSDM
2012
ACM
259views Data Mining» more  WSDM 2012»
13 years 5 months ago
Learning recommender systems with adaptive regularization
Many factorization models like matrix or tensor factorization have been proposed for the important application of recommender systems. The success of such factorization models dep...
Steffen Rendle
CVPR
2008
IEEE
16 years 15 hour ago
Conditional density learning via regression with application to deformable shape segmentation
Many vision problems can be cast as optimizing the conditional probability density function p(C|I) where I is an image and C is a vector of model parameters describing the image. ...
Jingdan Zhang, Shaohua Kevin Zhou, Dorin Comaniciu...
KDD
2002
ACM
157views Data Mining» more  KDD 2002»
15 years 10 months ago
Learning nonstationary models of normal network traffic for detecting novel attacks
Traditional intrusion detection systems (IDS) detect attacks by comparing current behavior to signatures of known attacks. One main drawback is the inability of detecting new atta...
Matthew V. Mahoney, Philip K. Chan
UM
2005
Springer
15 years 3 months ago
Modeling Individual and Collaborative Problem Solving in Medical Problem-Based Learning
Abstract. Since problem solving in group problem-based learning is a collaborative process, modeling individuals and the group is necessary if we wish to develop an intelligent tut...
Siriwan Suebnukarn, Peter Haddawy