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» Learning Relational Features with Backward Random Walks
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JCP
2008
121views more  JCP 2008»
14 years 11 months ago
Relation Organization of SOM Initial Map by Improved Node Exchange
The Self Organizing Map (SOM) involves neural networks, that learns the features of input data thorough unsupervised, competitive neighborhood learning. In the SOM learning algorit...
Tsutomu Miyoshi
ICCV
2009
IEEE
16 years 4 months ago
Body-Relative Navigation Guidance Using Uncalibrated Cameras
We present a vision-based method that assists human navigation within unfamiliar environments. Our main contribution is a novel algorithm that learns the correlation between use...
Olivier Koch, Seth Teller
COLING
2008
15 years 20 days ago
An Integrated Probabilistic and Logic Approach to Encyclopedia Relation Extraction with Multiple Features
We propose a new integrated approach based on Markov logic networks (MLNs), an effective combination of probabilistic graphical models and firstorder logic for statistical relatio...
Xiaofeng Yu, Wai Lam
ICML
2003
IEEE
16 years 12 hour ago
Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...
Xiaojin Zhu, Zoubin Ghahramani, John D. Lafferty
ICMCS
2009
IEEE
131views Multimedia» more  ICMCS 2009»
14 years 9 months ago
Web image mining using concept sensitive Markov stationary features
With the explosive growth of web resources, how to mine semantically relevant images efficiently becomes a challenging and necessary task. In this paper, we propose a concept sens...
Chunjie Zhang, Jing Liu, Hanqing Lu, Songde Ma