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» Learning the Structure of Dynamic Probabilistic Networks
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JMLR
2006
169views more  JMLR 2006»
13 years 7 months ago
Bayesian Network Learning with Parameter Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
CDC
2008
IEEE
142views Control Systems» more  CDC 2008»
14 years 2 months ago
Convergence of rule-of-thumb learning rules in social networks
— We study the problem of dynamic learning by a social network of agents. Each agent receives a signal about an underlying state and communicates with a subset of agents (his nei...
Daron Acemoglu, Angelia Nedic, Asuman E. Ozdaglar
RECOMB
2007
Springer
14 years 8 months ago
A Feature-Based Approach to Modeling Protein-DNA Interactions
Transcription factor (TF) binding to its DNA target site is a fundamental regulatory interaction. The most common model used to represent TF binding specificities is a position spe...
Eilon Sharon, Eran Segal
IJON
2008
156views more  IJON 2008»
13 years 7 months ago
Analysis of the dynamical behavior of a feedback auto-associative memory
The dynamical behavior and the stability properties of fixed points in a feedback auto-associative memory are investigated. The proposed structure encompasses a multi-layer percep...
Mahmood Amiri, Sohrab Saeb, Mohammad Javad Yazdanp...
HUC
2010
Springer
13 years 7 months ago
Bayesian recognition of motion related activities with inertial sensors
This work presents the design and evaluation of an activity recognition system for seven important motion related activities. The only sensor used is an Inertial Measurement Unit ...
Korbinian Frank, Maria Josefa Vera Nadales, Patric...