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Now showing items 33-52 of 310

Beyond Prototypes and Frames: The Two-tiered Concept Representation

Michalski, Ryszard S. (1992)
Beyond Prototypes and Frames: The Two-tiered Concept Representation

Michalski, Ryszard S. (1991-09)
A Brief Review of AQ Learning Programs and Their Application to the MONKS Problems

Bala, Jerzy W.; Bloedorn, Eric; De Jong, Kenneth A.; Kaufman, Kenneth A.; Michalski, Ryszard S.; Pachowicz, Peter W.; Vafaie, Haleh; Wnek, Janusz; Zhang, Jianping (1992-02-10)
Building Knowledge Scouts Using KGL Metalanguage

Michalski, Ryszard S.; Kaufman, Kenneth A. (2000)

Knowledge scouts are software agents that autonomously search for and synthesize user-oriented knowledge (target knowledge) in large local or distributed databases. A knowledge generation metalanguage, KGL, is used to ...
Can comprehensive geriatric assessment compared with standard care help predict and prevent falls among older adults?

John, Ellen (George Mason University, 2013-06-20)

Purpose: To find out if comprehensive geriatric assessment can help predict and prevent falls among the older adults.
Center for Machine Learning and Inference: An Overview of Research and Activities

Michalski, Ryszard S. (1995-01)
Challenges to the Systematic Adoption of Person-Centered Planning

Wolf-Branigin, Michael; LeRoy, Barbara; Wolf-Branigin, Karen; Israel, Nathaniel; Kulik, Noel (2007)

Previous reviews of person-centered planning indicate a need for more comprehensive training to promote skill generalization. A three-phase training intervention was implemented with 22 planning teams for people with a ...
Combining Machine Learning with Evolutionary Computation: Recent Results on LEM

Cervone, Guido; Michalski, Ryszard S.; Kaufman, Kenneth A.; Panait, Liviu A. (2000-06)

The Learnable Evolution Model (LEM), first presented at the Fourth International Workshop on Multistrategy Learning, employs machine learing to guide evolutionary computation. Specifically, LEM integrates two modes of ...
A Comparative Review of Selected Methods for Learning from Examples

Dieterrich, Thomas G.; Michalski, Ryszard S. (1983)
Comparing Learning Paradigms via Diagrammatic Visualization: A Case Study in Concept Learning Using Symbolic, Neural Net and Genetic Algorithm Methods

Wnek, Janusz; Sarma, Jayshree; Wahab, Ashraf A.; Michalski, Ryszard S. (1990-10)
Comparing Learning Paradigms via Diagrammatic Visualization: A Case Study in Single Concept Learning using Symbolic, Neural Net and Genetic Algorithm Methods

Wnek, Janusz; Sarma, Jayshree; Wahab, Ashraf A.; Michalski, Ryszard S. (1990-01)
Comparing Symbolic and Subsymbolic Learning: Three Studies

Wnek, Janusz; Michalski, Ryszard S. (1992-10)
Complexities in Attracting and Retaining Direct Support Professionals

Wolf-Branigin, Michael; Wolf-Branigin, Karen; Israel, Nathaniel (2007)

Recruiting and retaining direct support professionals (DSPs) remains essential to the full inclusion for persons with disabilities. Using a mixed-evaluation model, we measured DSPs’ views versus those of their supervisors. ...
Computer Vision through Learning

Maloof, Marcus A.; Rosenfeld, Azriel; Duric, Zoran; Aloimonos, Yiannis; Zhang, Qi; Michalski, Ryszard S. (1997)
Concept-based Clustering versus Numerical Taxonomy

Stepp, Robert E.; Michalski, Ryszard S. (1981-10)
Concepts as Flexible and Context-dependent Sets: the two-tiered view

Michalski, Ryszard S. (1991)
Conceptual Clustering: A Theoretical Foundation and a Method for Partitioning Data into Conjunctive Concepts

Michalski, Ryszard S. (1979)
Conceptual Clustering: Inventing Goal-Oriented Classifications of Structured Objects

Stepp, Robert E.; Michalski, Ryszard S. (1986)
Conceptual Transition from Logic to Arithmetic

Wnek, Janusz; Michalski, Ryszard S. (1994-12)
Conjunctive Conceptual Clustering: Classification Using Background Knowledge

Stepp, Robert E.; Michalski, Ryszard S. (1983-05)

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