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Browsing College of Health and Human Services by Author "Wojtusiak, Janusz"

Browsing College of Health and Human Services by Author "Wojtusiak, Janusz"

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  • Wojtusiak, Janusz (2006-07)
    Learnable Evolution Model (LEM) is an evolutionary computation methodology that applies hypothesis formulation and instantiation to create new individuals. Initial study has shown that LEM significantly outperforms standard ...
  • Michalski, Ryszard S.; Kaufman, Kenneth A.; Pietrzykowski, Jaroslaw; Śnieżyński, Bartłomiej; Wojtusiak, Janusz (2006-06)
    This paper briefly describes the LUS-MT method for automatically learning user signatures (models of computer users) from datastreams capturing users’ interactions with computers. The signatures are in the form of collections ...
  • Michalski, Ryszard S.; Kaufman, Kenneth A.; Pietrzykowski, Jaroslaw; Śnieżyński, Bartłomiej; Wojtusiak, Janusz (2005-11)
    This paper presents a description of the LUS method for creating models (signatures) of computer users from datastreams that characterize users' interactions with computers, and the results of initial experiments with this ...
  • Wojtusiak, Janusz; Michalski, Ryszard S. (2006-07)
    Learnable Evolution Model (LEM) is a form of non-Darwinian evolutionary computation that employs machine learning to guide evolutionary processes. Its main novelty are new types of operators for creating new individuals, ...
  • Wojtusiak, Janusz; Michalski, Ryszard S. (2005-10)
    LEM3 is the newest implementation of Learnable Evolution Model (LEM), a non-Darwinian evolutionary computation methodology that employs machine learning to guide evolutionary processes. Due to a deep integration of different ...
  • Wojtusiak, Janusz; Michalski, Ryszard S.; Kaufman, Kenneth A.; Pietrzykowski, Jaroslaw (2006-06)
    The AQ21 program seeks different types of patterns in data and represents them in human-oriented forms resembling natural language descriptions. Because of the latter feature it is called a natural induction program. This ...
  • Michalski, Ryszard S.; Kaufman, Kenneth A.; Pietrzykowski, Jaroslaw; Wojtusiak, Janusz; Mitchell, Scott; Seeman, Doug (2006-06)
    Natural induction and conceptual clustering are two methodologies pioneered by the GMU Machine Learning and Inference Laboratory for discovering conceptual relationships in data, and presenting them in the forms easy for ...
  • Michalski, Ryszard S.; Wojtusiak, Janusz; Kaufman, Kenneth (2007-11-18)
    This report reviews recent research on Learnable Evolution Model (LEM), and presents selected results from its application to the optimization of complex functions and engineering designs. Among the most significant new ...
  • Michalski, Ryszard S.; Wojtusiak, Janusz (2005-06)
    This paper describes methods for reasoning with missing, irrelevant and not applicable meta-values in the AQ attributional rule learning. The methods address issues of handling these values in datasets both for rule learning ...
  • Michalski, Ryszard S.; Wojtusiak, Janusz (2007-11-18)
    AQ learning strives to perform natural induction that aims at deriving general descriptions from specific data and formulating them in human-oriented forms. Such descriptions are in the forms closely corresponding to simple ...
  • Wojtusiak, Janusz; Michalski, Ryszard S. (2006-06)
    Compound attributes are named groups of attributes that have been introduced in Attributional Calculus (AC) to facilitate learning descriptions of objects whose components are characterized by different subsets of attributes. ...

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