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» Structural Machine Learning with Galois Lattice and Graphs
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ALT
2008
Springer
15 years 6 months ago
Exploiting Cluster-Structure to Predict the Labeling of a Graph
Abstract. The nearest neighbor and the perceptron algorithms are intuitively motivated by the aims to exploit the “cluster” and “linear separation” structure of the data to...
Mark Herbster
ICALT
2009
IEEE
15 years 4 months ago
Korean Word Associations: The Linked Structures for Language Learning
This paper reports on Korean Word Associations (KorWA) which were collected to construct a semantic network for Korean language. An approach of graph representation and network an...
Jaeyoung Jung, Nobuyasu Makoshi, Hiroyuki Akama
ICMLA
2009
14 years 7 months ago
Exact Graph Structure Estimation with Degree Priors
We describe a generative model for graph edges under specific degree distributions which admits an exact and efficient inference method for recovering the most likely structure. T...
Bert Huang, Tony Jebara
ILP
2007
Springer
15 years 3 months ago
Structural Statistical Software Testing with Active Learning in a Graph
Structural Statistical Software Testing (SSST) exploits the control flow graph of the program being tested to construct test cases. Specifically, SSST exploits the feasible paths...
Nicolas Baskiotis, Michèle Sebag
ICCS
1993
Springer
15 years 1 months ago
Towards Domain-Independent Machine Intelligence
Adaptive predictive search (APS), is a learning system framework, which given little initial domain knowledge, increases its decision-making abilities in complex problems domains....
Robert Levinson