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» Object correspondence as a machine learning problem
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ICML
2005
IEEE
16 years 2 months ago
Discriminative versus generative parameter and structure learning of Bayesian network classifiers
In this paper, we compare both discriminative and generative parameter learning on both discriminatively and generatively structured Bayesian network classifiers. We use either ma...
Franz Pernkopf, Jeff A. Bilmes
ICFCA
2009
Springer
15 years 6 months ago
A Novel Approach to Cell Formation
We present an approach to the cell formation problem, known from group technology, which is inspired by formal concept analysis. The cell formation problem consists in allocating p...
Radim Belohlávek, Niranjan Kulkarni, Vil&ea...
ICML
2007
IEEE
16 years 2 months ago
Statistical predicate invention
We propose statistical predicate invention as a key problem for statistical relational learning. SPI is the problem of discovering new concepts, properties and relations in struct...
Stanley Kok, Pedro Domingos
PR
2007
81views more  PR 2007»
15 years 1 months ago
Graph embedding using tree edit-union
In this paper we address the problem of how to learn a structural prototype that can be used to represent the variations present in a set of trees. The prototype serves as a patte...
Andrea Torsello, Edwin R. Hancock
EELC
2006
121views Languages» more  EELC 2006»
15 years 5 months ago
Symbol Grounding Through Cumulative Learning
Abstract. We suggest that the primary motivation for an agent to construct a symbol-meaning mapping is to solve a task. The meaning space of an agent should be derived from the tas...
Samarth Swarup, Kiran Lakkaraju, Sylvian R. Ray, L...