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» Learning the Common Structure of Data
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ICML
1997
IEEE
14 years 11 months ago
Learning Belief Networks in the Presence of Missing Values and Hidden Variables
In recent years there has been a flurry of works on learning probabilistic belief networks. Current state of the art methods have been shown to be successful for two learning scen...
Nir Friedman
ECCV
2002
Springer
15 years 21 days ago
Multimodal Data Representations with Parameterized Local Structures
Abstract. In many vision problems, the observed data lies in a nonlinear manifold in a high-dimensional space. This paper presents a generic modelling scheme to characterize the no...
Ying Zhu, Dorin Comaniciu, Stuart C. Schwartz, Vis...
BIOCOMP
2006
14 years 7 days ago
Dynamic Bayesian Network (DBN) with Structure Expectation Maximization (SEM) for Modeling of Gene Network from Time Series Gene
Exploring gene regulatory network is a key topic in molecular biology. In this paper, we present a new dynamic Bayesian network (DBN) framework embedded with structural expectatio...
Yu Zhang, Zhidong Deng, Hongshan Jiang, Peifa Jia
EMNLP
2010
13 years 8 months ago
Efficient Graph-Based Semi-Supervised Learning of Structured Tagging Models
We describe a new scalable algorithm for semi-supervised training of conditional random fields (CRF) and its application to partof-speech (POS) tagging. The algorithm uses a simil...
Amarnag Subramanya, Slav Petrov, Fernando Pereira
ICCS
2007
Springer
14 years 2 months ago
Discovering Latent Structures: Experience with the CoIL Challenge 2000 Data Set
We present a case study to demonstrate the possibility of discovering complex and interesting latent structures using hierarchical latent class (HLC) models. A similar effort was m...
Nevin Lianwen Zhang