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ICML
2009
IEEE
14 years 9 months ago
Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
There has been much interest in unsupervised learning of hierarchical generative models such as deep belief networks. Scaling such models to full-sized, high-dimensional images re...
Honglak Lee, Roger Grosse, Rajesh Ranganath, Andre...
CI
2011
93views more  CI 2011»
13 years 3 months ago
Supporting clinical processes and decisions by hierarchical planning and scheduling
This paper is focused on how a general-purpose hierarchical planning representation, based on the HTN paradigm, can be used to support the representation of oncology treatment pro...
Juan Fernández-Olivares, Luis A. Castillo, ...
KDD
2010
ACM
233views Data Mining» more  KDD 2010»
14 years 19 days ago
Evolutionary hierarchical dirichlet processes for multiple correlated time-varying corpora
Mining cluster evolution from multiple correlated time-varying text corpora is important in exploratory text analytics. In this paper, we propose an approach called evolutionary h...
Jianwen Zhang, Yangqiu Song, Changshui Zhang, Shix...
IJON
2010
189views more  IJON 2010»
13 years 7 months ago
Inference and parameter estimation on hierarchical belief networks for image segmentation
We introduce a new causal hierarchical belief network for image segmentation. Contrary to classical tree structured (or pyramidal) models, the factor graph of the network contains...
Christian Wolf, Gérald Gavin
WWW
2007
ACM
14 years 9 months ago
Hierarchical, perceptron-like learning for ontology-based information extraction
Recent work on ontology-based Information Extraction (IE) has tried to make use of knowledge from the target ontology in order to improve semantic annotation results. However, ver...
Yaoyong Li, Kalina Bontcheva