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ML
2006
ACM
131views Machine Learning» more  ML 2006»
13 years 5 months ago
Markov logic networks
We propose a simple approach to combining first-order logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a first-order knowledge b...
Matthew Richardson, Pedro Domingos
ITS
2004
Springer
110views Multimedia» more  ITS 2004»
13 years 11 months ago
Scaffolding Self-Explanation to Improve Learning in Exploratory Learning Environments.
Abstract. Successful learning though exploration in open learning environments has been shown to depend on whether students possess the necessary meta-cognitive skills, including s...
Andrea Bunt, Cristina Conati, Kasia Muldner
MLDM
2009
Springer
14 years 9 days ago
An Evidence-Driven Probabilistic Inference Framework for Semantic Image Understanding
This work presents an image analysis framework driven by emerging evidence and constrained by the semantics expressed in an ontology. Human perception, apart from visual stimulus a...
Spiros Nikolopoulos, Georgios Th. Papadopoulos, Io...
NIPS
2004
13 years 7 months ago
Semi-supervised Learning with Penalized Probabilistic Clustering
While clustering is usually an unsupervised operation, there are circumstances in which we believe (with varying degrees of certainty) that items A and B should be assigned to the...
Zhengdong Lu, Todd K. Leen
AAAI
2008
13 years 8 months ago
Structure Learning on Large Scale Common Sense Statistical Models of Human State
Research has shown promise in the design of large scale common sense probabilistic models to infer human state from environmental sensor data. These models have made use of mined ...
William Pentney, Matthai Philipose, Jeff A. Bilmes