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JMLR
2012
11 years 8 months ago
Approximate Inference in Additive Factorial HMMs with Application to Energy Disaggregation
This paper considers additive factorial hidden Markov models, an extension to HMMs where the state factors into multiple independent chains, and the output is an additive function...
J. Zico Kolter, Tommi Jaakkola
NN
1997
Springer
174views Neural Networks» more  NN 1997»
13 years 10 months ago
Learning Dynamic Bayesian Networks
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
Zoubin Ghahramani
EDM
2010
160views Data Mining» more  EDM 2010»
13 years 7 months ago
Using Neural Imaging and Cognitive Modeling to Infer Mental States while Using an Intelligent Tutoring System
Functional magnetic resonance imaging (fMRI) data were collected while students worked with a tutoring system that taught an algebra isomorph. A cognitive model predicted the distr...
Jon M. Fincham, John R. Anderson, Shawn Betts, Jen...
ESSMAC
2003
Springer
13 years 11 months ago
Simultaneous Localization and Surveying with Multiple Agents
We apply a constrained Hidden Markov Model architecture to the problem of simultaneous localization and surveying from sensor logs of mobile agents navigating in unknown environmen...
Sam T. Roweis, Ruslan Salakhutdinov
ICASSP
2009
IEEE
13 years 10 months ago
Graphical Models: Statistical inference vs. determination
Using discrete Hidden-Markov-Models (HMMs) for recognition requires the quantization of the continuous feature vectors. In handwritten whiteboard note recognition it turns out tha...
Joachim Schenk, Benedikt Hörnler, Artur Braun...