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» Two Algorithms for Inducing Causal Models from Data
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TASLP
2011
14 years 4 months ago
A Probabilistic Interaction Model for Multipitch Tracking With Factorial Hidden Markov Models
—We present a simple and efficient feature modeling approach for tracking the pitch of two simultaneously active speakers. We model the spectrogram features of single speakers u...
Michael Wohlmayr, Michael Stark, Franz Pernkopf
UAI
1996
14 years 11 months ago
Bayesian Learning of Loglinear Models for Neural Connectivity
This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...
Kathryn B. Laskey, Laura Martignon
BMCBI
2008
121views more  BMCBI 2008»
14 years 10 months ago
Microarray data mining using landmark gene-guided clustering
Background: Clustering is a popular data exploration technique widely used in microarray data analysis. Most conventional clustering algorithms, however, generate only one set of ...
Pankaj Chopra, Jaewoo Kang, Jiong Yang, HyungJun C...
AAAI
2006
14 years 11 months ago
Decision Tree Methods for Finding Reusable MDP Homomorphisms
straction is a useful tool for agents interacting with environments. Good state abstractions are compact, reuseable, and easy to learn from sample data. This paper and extends two...
Alicia P. Wolfe, Andrew G. Barto
NIPS
2003
14 years 11 months ago
Computing Gaussian Mixture Models with EM Using Equivalence Constraints
Density estimation with Gaussian Mixture Models is a popular generative technique used also for clustering. We develop a framework to incorporate side information in the form of e...
Noam Shental, Aharon Bar-Hillel, Tomer Hertz, Daph...