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» Learning and Generalization with the Information Bottleneck
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MM
2003
ACM
84views Multimedia» more  MM 2003»
15 years 12 months ago
Temporal event clustering for digital photo collections
We present similarity-based methods to cluster digital photos by time and image content. The approach is general, unsupervised, and makes minimal assumptions regarding the structu...
Matthew L. Cooper, Jonathan Foote, Andreas Girgens...
ECCV
2006
Springer
16 years 8 months ago
Statistical Priors for Efficient Combinatorial Optimization Via Graph Cuts
Abstract. Bayesian inference provides a powerful framework to optimally integrate statistically learned prior knowledge into numerous computer vision algorithms. While the Bayesian...
Daniel Cremers, Leo Grady
ICIP
2008
IEEE
16 years 8 months ago
A supervised nonlinear neighborhood embedding of color histogram for image indexing
Subspace learning techniques are widespread in pattern recognition research. They include PCA, ICA, LPP, etc. These techniques are generally linear and unsupervised. The problem o...
Xian-Hua Han, Yen-Wei Chen, Takeshi Sukegawa
IUI
2006
ACM
16 years 18 days ago
Are two talking heads better than one?: when should use more than one agent in e-learning?
Recent interest in the use of software character agents raises the issue of how many agents should be used in online learning. In this paper we review evidence concerning the rela...
Hua Wang, Mark H. Chignell, Mitsuru Ishizuka
ICALT
2003
IEEE
15 years 12 months ago
Initializing Student Models in Web-Based ITSs: A Generic Approach
The issue of initializing the model of a new student is of great importance for educational applications that aim at offering individualized support to students. In this paper we ...
Victoria Tsiriga, Maria Virvou