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NIPS
2000
13 years 11 months ago
Active Learning for Parameter Estimation in Bayesian Networks
Bayesian networks are graphical representations of probability distributions. In virtually all of the work on learning these networks, the assumption is that we are presented with...
Simon Tong, Daphne Koller
VLSID
2005
IEEE
255views VLSI» more  VLSID 2005»
14 years 10 months ago
Estimation of Switching Activity in Sequential Circuits Using Dynamic Bayesian Networks
We propose a novel, non-simulative, probabilistic model for switching activity in sequential circuits, capturing both spatio-temporal correlations at internal nodes and higher ord...
Sanjukta Bhanja, Karthikeyan Lingasubramanian, N. ...
UAI
2003
13 years 11 months ago
The Revisiting Problem in Mobile Robot Map Building: A Hierarchical Bayesian Approach
We present an application of hierarchical Bayesian estimation to robot map building. The revisiting problem occurs when a robot has to decide whether it is seeing a previously-bui...
Benjamin Stewart, Jonathan Ko, Dieter Fox, Kurt Ko...
AAAI
1997
13 years 11 months ago
Effective Bayesian Inference for Stochastic Programs
In this paper, we propose a stochastic version of a general purpose functional programming language as a method of modeling stochastic processes. The language contains random choi...
Daphne Koller, David A. McAllester, Avi Pfeffer
ICDAR
2003
IEEE
14 years 2 months ago
Generation of Handwritten Characters with Bayesian network based On-line Handwriting Recognizers
In this paper, we propose a new character generation method from on-line handwriting recognizers based on Bayesian networks. On-line handwriting recognizers are trained with handw...
Hyun-Il Choi, Sung-Jung Cho, Jin Hyung Kim