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» Hidden Markov Models with Multiple Observation Processes
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PERCOM
2007
ACM
16 years 3 months ago
The Role of Probabilistic Schemes in Multisensor Context-Awareness
This paper investigates the role of existing "probabilistic" schemes to reason about various everyday situations on the basis of data from multiple heterogeneous physical...
Waltenegus Dargie
BMCBI
2007
98views more  BMCBI 2007»
15 years 4 months ago
Duration learning for analysis of nanopore ionic current blockades
Background: Ionic current blockade signal processing, for use in nanopore detection, offers a promising new way to analyze single molecule properties, with potential implications ...
Alexander G. Churbanov, Carl Baribault, Stephen Wi...
JMLR
2008
188views more  JMLR 2008»
15 years 3 months ago
Maximal Causes for Non-linear Component Extraction
We study a generative model in which hidden causes combine competitively to produce observations. Multiple active causes combine to determine the value of an observed variable thr...
Jörg Lücke, Maneesh Sahani
180
Voted
CVPR
2011
IEEE
15 years 5 days ago
Clues from the Beaten Path: Location Estimation with Bursty Sequences of Tourist Photos
Image-based location estimation methods typically recognize every photo independently, and their resulting reliance on strong visual feature matches makes them most suited for dis...
Chao-Yeh Chen, Kristen Grauman
128
Voted
COMPLEX
2009
Springer
15 years 8 months ago
Non-sufficient Memories That Are Sufficient for Prediction
The causal states of computational mechanics define the minimal sufficient (prescient) memory for a given stationary stochastic process. They induce the -machine which is a hidden...
Wolfgang Löhr, Nihat Ay