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» Dynamic Modeling in Inductive Inference
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AUSAI
2009
Springer
14 years 2 months ago
Information-Theoretic Image Reconstruction and Segmentation from Noisy Projections
The minimum message length (MML) principle for inductive inference has been successfully applied to image segmentation where the images are modelled by Markov random fields (MRF)....
Gerhard Visser, David L. Dowe, Imants D. Svalbe
ICCBR
2003
Springer
14 years 1 months ago
Combining Case-Based and Model-Based Reasoning for Predicting the Outcome of Legal Cases
This paper presents an algorithm called IBP that combines case-based and model-based reasoning for an interpretive CBR application, predicting the outcome of legal cases. IBP uses ...
Stefanie Brüninghaus, Kevin D. Ashley
ALT
2003
Springer
14 years 4 months ago
Intrinsic Complexity of Uniform Learning
Inductive inference is concerned with algorithmic learning of recursive functions. In the model of learning in the limit a learner successful for a class of recursive functions mus...
Sandra Zilles
CVPR
1999
IEEE
14 years 10 months ago
Time-Series Classification Using Mixed-State Dynamic Bayesian Networks
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huan...
AGP
2003
IEEE
13 years 11 months ago
Using dynamic logic programming to model legal reasoning
Dynamic logic programming allows the representation and the inference of evolving knowledge. Legal knowledge reasoning needs the capability to model laws that change over time and ...
N. Graca, Paulo Quaresma