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» Generalization Improvement in Multi-Objective Learning
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85
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GECCO
2007
Springer
187views Optimization» more  GECCO 2007»
15 years 6 months ago
Defining implicit objective functions for design problems
In many design tasks it is difficult to explicitly define an objective function. This paper uses machine learning to derive an objective in a feature space based on selected examp...
Sean Hanna
91
Voted
MLDM
2007
Springer
15 years 6 months ago
PE-PUC: A Graph Based PU-Learning Approach for Text Classification
This paper presents a novel solution for the problem of building text classifier using positive documents (P) and unlabeled documents (U). Here, the unlabeled documents are mixed w...
Shuang Yu, Chunping Li
85
Voted
GECCO
2005
Springer
130views Optimization» more  GECCO 2005»
15 years 6 months ago
ATNoSFERES revisited
ATNoSFERES is a Pittsburgh style Learning Classifier System (LCS) in which the rules are represented as edges of an Augmented Transition Network. Genotypes are strings of tokens ...
Samuel Landau, Olivier Sigaud, Marc Schoenauer
89
Voted
ISAAC
2005
Springer
138views Algorithms» more  ISAAC 2005»
15 years 6 months ago
On the Complexity of Rocchio's Similarity-Based Relevance Feedback Algorithm
In this paper, we prove for the first time that the learning complexity of Rocchio’s algorithm is O(d+d2 (log d+log n)) over the discretized vector space {0, . . . , n − 1}d ,...
Zhixiang Chen, Bin Fu
SIGIR
2003
ACM
15 years 5 months ago
Text categorization by boosting automatically extracted concepts
Term-based representations of documents have found widespread use in information retrieval. However, one of the main shortcomings of such methods is that they largely disregard le...
Lijuan Cai, Thomas Hofmann