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ICML
2005
IEEE
14 years 11 months ago
Reducing overfitting in process model induction
In this paper, we review the paradigm of inductive process modeling, which uses background knowledge about possible component processes to construct quantitative models of dynamic...
Will Bridewell, Narges Bani Asadi, Pat Langley, Lj...
ICML
2005
IEEE
14 years 11 months ago
Learning the structure of Markov logic networks
Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as templates for features of Markov networks. In this pap...
Stanley Kok, Pedro Domingos
KDD
2003
ACM
150views Data Mining» more  KDD 2003»
14 years 11 months ago
Learning relational probability trees
Classification trees are widely used in the machine learning and data mining communities for modeling propositional data. Recent work has extended this basic paradigm to probabili...
Jennifer Neville, David Jensen, Lisa Friedland, Mi...
VLDB
2007
ACM
159views Database» more  VLDB 2007»
14 years 11 months ago
Example-driven design of efficient record matching queries
Record matching is the task of identifying records that match the same real world entity. This is a problem of great significance for a variety of business intelligence applicatio...
Surajit Chaudhuri, Bee-Chung Chen, Venkatesh Ganti...
SIGMOD
2004
ACM
127views Database» more  SIGMOD 2004»
14 years 11 months ago
Efficient Query Reformulation in Peer-Data Management Systems
Peer data management systems (PDMS) offer a flexible architecture for decentralized data sharing. In a PDMS, every peer is associated with a schema that represents the peer's...
Igor Tatarinov, Alon Y. Halevy