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IBPRIA
2007
Springer
15 years 6 months ago
Automatic Learning of Conceptual Knowledge in Image Sequences for Human Behavior Interpretation
This work describes an approach for the interpretation and explanation of human behavior in image sequences, within the context of a Cognitive Vision System. The information source...
Pau Baiget, Carles Fernández Tena, F. Xavie...
PKDD
2004
Springer
155views Data Mining» more  PKDD 2004»
15 years 10 months ago
Ensemble Feature Ranking
A crucial issue for Machine Learning and Data Mining is Feature Selection, selecting the relevant features in order to focus the learning search. A relaxed setting for Feature Sele...
Kees Jong, Jérémie Mary, Antoine Cor...
156
Voted
KDD
2009
ACM
224views Data Mining» more  KDD 2009»
15 years 9 months ago
Issues in evaluation of stream learning algorithms
Learning from data streams is a research area of increasing importance. Nowadays, several stream learning algorithms have been developed. Most of them learn decision models that c...
João Gama, Raquel Sebastião, Pedro P...
SOCIALCOM
2010
15 years 2 months ago
Mining Human Location-Routines Using a Multi-Level Approach to Topic Modeling
In this work we address the problem of modeling varying time duration sequences for large-scale human routine discovery from cellphone sensor data using a multi-level approach to p...
Katayoun Farrahi, Daniel Gatica-Perez
AAAI
2008
15 years 7 months ago
Latent Tree Models and Approximate Inference in Bayesian Networks
We propose a novel method for approximate inference in Bayesian networks (BNs). The idea is to sample data from a BN, learn a latent tree model (LTM) from the data offline, and wh...
Yi Wang, Nevin Lianwen Zhang, Tao Chen