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» Unsupervised learning of probabilistic object models (POMs) ...
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CVPR
2009
IEEE
14 years 11 months ago
Co-training with Noisy Perceptual Observations
Many perception and multimedia indexing problems involve datasets that are naturally comprised of multiple streams or modalities for which supervised training data is only sparsely...
Ashish Kapoor, Chris Mario Christoudias, Raquel Ur...
UAI
2003
13 years 6 months ago
On the Convergence of Bound Optimization Algorithms
Many practitioners who use EM and related algorithms complain that they are sometimes slow. When does this happen, and what can be done about it? In this paper, we study the gener...
Ruslan Salakhutdinov, Sam T. Roweis, Zoubin Ghahra...
SIGIR
2005
ACM
13 years 10 months ago
A database centric view of semantic image annotation and retrieval
We introduce a new model for semantic annotation and retrieval from image databases. The new model is based on a probabilistic formulation that poses annotation and retrieval as c...
Gustavo Carneiro, Nuno Vasconcelos
NIPS
2008
13 years 6 months ago
Natural Image Denoising with Convolutional Networks
We present an approach to low-level vision that combines two main ideas: the use of convolutional networks as an image processing architecture and an unsupervised learning procedu...
Viren Jain, H. Sebastian Seung
GBRPR
2007
Springer
13 years 8 months ago
An Efficient Ontology-Based Expert Peering System
Abstract. This paper proposes an expert peering system for information exchange. Our objective is to develop a real-time search engine for an online community where users can ask e...
Tansu Alpcan, Christian Bauckhage, Sachin Agarwal