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ICML
2008
IEEE
16 years 5 months ago
Modeling interleaved hidden processes
Hidden Markov models assume that observations in time series data stem from some hidden process that can be compactly represented as a Markov chain. We generalize this model by as...
Niels Landwehr
ICML
2006
IEEE
16 years 5 months ago
Dynamic topic models
A family of probabilistic time series models is developed to analyze the time evolution of topics in large document collections. The approach is to use state space models on the n...
David M. Blei, John D. Lafferty
ICML
2005
IEEE
16 years 5 months ago
Modeling word burstiness using the Dirichlet distribution
Multinomial distributions are often used to model text documents. However, they do not capture well the phenomenon that words in a document tend to appear in bursts: if a word app...
Rasmus Elsborg Madsen, David Kauchak, Charles Elka...
ICML
2001
IEEE
16 years 5 months ago
Using EM to Learn 3D Models of Indoor Environments with Mobile Robots
This paper describes an algorithm for generating compact 3D models of indoor environments with mobile robots. Our algorithm employs the expectation maximization algorithm to fit a...
Yufeng Liu, Rosemary Emery, Deepayan Chakrabarti, ...
CHI
2006
ACM
16 years 5 months ago
Comparisons of keystroke-level model predictions to observed data
Comparison of model prediction against observed data is an investigative step used in cognitive modeling research for human-computer interaction. In this paper we describe compari...
Leonghwee Teo, Bonnie E. John
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