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» Constraint Programming for Data Mining and Machine Learning
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ACL
2009
14 years 11 months ago
Concise Integer Linear Programming Formulations for Dependency Parsing
We formulate the problem of nonprojective dependency parsing as a polynomial-sized integer linear program. Our formulation is able to handle non-local output features in an effici...
André L. Martins, Noah A. Smith, Eric P. Xi...
KDD
2005
ACM
143views Data Mining» more  KDD 2005»
16 years 2 months ago
SVM selective sampling for ranking with application to data retrieval
Learning ranking (or preference) functions has been a major issue in the machine learning community and has produced many applications in information retrieval. SVMs (Support Vect...
Hwanjo Yu
ICDM
2005
IEEE
116views Data Mining» more  ICDM 2005»
15 years 7 months ago
Learning Functional Dependency Networks Based on Genetic Programming
Bayesian Network (BN) is a powerful network model, which represents a set of variables in the domain and provides the probabilistic relationships among them. But BN can handle dis...
Wing-Ho Shum, Kwong-Sak Leung, Man Leung Wong
AUSAI
2005
Springer
15 years 7 months ago
K-Optimal Pattern Discovery: An Efficient and Effective Approach to Exploratory Data Mining
Most data-mining techniques seek a single model that optimizes an objective function with respect to the data. In many real-world applications several models will equally optimize...
Geoffrey I. Webb
MLG
2007
Springer
15 years 8 months ago
Improving Frequent Subgraph Mining in the Presence of Symmetry
While recent algorithms for mining the frequent subgraphs of a database are efficient in the general case, these algorithms tend to do poorly on databases that have a few or no la...
Christian Desrosiers, Philippe Galinier, Pierre Ha...