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ICML
2010
IEEE
15 years 8 months ago
Hilbert Space Embeddings of Hidden Markov Models
Hidden Markov Models (HMMs) are important tools for modeling sequence data. However, they are restricted to discrete latent states, and are largely restricted to Gaussian and disc...
Le Song, Sajid M. Siddiqi, Geoffrey J. Gordon, Ale...
CSDA
2006
83views more  CSDA 2006»
15 years 7 months ago
Linear grouping using orthogonal regression
A new method to detect different linear structures in a data set, called Linear Grouping Algorithm (LGA), is proposed. LGA is useful for investigating potential linear patterns in...
Stefan Van Aelst, Xiaogang Wang, Ruben H. Zamar, R...
IJRR
2007
186views more  IJRR 2007»
15 years 7 months ago
Extracting Places and Activities from GPS Traces Using Hierarchical Conditional Random Fields
Learning patterns of human behavior from sensor data is extremely important for high-level activity inference. We show how to extract a person’s activities and significant plac...
Lin Liao, Dieter Fox, Henry A. Kautz
TSI
2008
89views more  TSI 2008»
15 years 7 months ago
RedGRID, un environnement pour la redistribution d'objets complexes
In the context of code coupling, efficient data redistribution is a crucial issue to reach high-performances. However, most of the works in this area have limited their studies to ...
Aurélien Esnard
CACM
2000
121views more  CACM 2000»
15 years 7 months ago
A broader approach to personalization
data model provides an abstract, conceptual framework; a concrete syntax is also required and XML is used for this purpose. The XML namespace mechanism serves to identify RDF Schem...
Ibrahim Cingil, Asuman Dogac, Ayca Azgin