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標題: Titlebook: Machine Learning of Inductive Bias; Paul E. Utgoff Book 1986 Kluwer Academic Publishers 1986 grammar.knowledge.knowledge base.learning.mac [打印本頁]

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書目名稱Machine Learning of Inductive Bias讀者反饋學科排名





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Machine Learning of Inductive Bias978-1-4613-2283-2Series ISSN 0893-3405
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LEX and STABB,line for testing ideas and for exposing unexpected problems. This chapter describes the learning program LEX[36] and shows how STABB has been made a subsystem of LEX. With STABB, LEX can shift its bias. Chapters 5 and 6 describe the two algorithms used by STABB, each employing the RTA Method.
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The Springer International Series in Engineering and Computer Sciencehttp://image.papertrans.cn/m/image/620708.jpg
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Related Work,This chapter shows the role of bias in several well known learning programs. The first section includes those programs that do not change the bias during concept learning. The second section shows the only two programs known to the author that do change the bias during concept learning.
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Introduction,resumed to require intelligence. This work includes problem solving, game playing, theorem proving, reasoning, speech understanding, vision, natural language processing, and knowledge-based expert systems. One important dimension of this work is that some of the programs that mimic intelligence are
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LEX and STABB,line for testing ideas and for exposing unexpected problems. This chapter describes the learning program LEX[36] and shows how STABB has been made a subsystem of LEX. With STABB, LEX can shift its bias. Chapters 5 and 6 describe the two algorithms used by STABB, each employing the RTA Method.
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Paul E. Utgoffsurface parameters. This information can be gained from the measured spectra employing so-called inverse theory and the problem to be solved thereby is usually referred to as the inverse problem. The first step to be done in the solution of any inverse problem is to formulate a model usually referre
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Paul E. Utgoff, immediately after the invention of the laser, and since then they have been actively used in the problems of natural media monitoring. Lidars are of great use in providing atmosphere and ocean pollution control, in control of atmospheric gases, and in measuring meteorological and climate character
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0893-3405 e Department of Computer Science at Rutgers University. The book was pre- pared at the University of Massachusetts at Amherst where the author is currently an Assistant Professor in the Department of Computer and Infor- mation Science. Programs that learn concepts from examples are guided not only b
作者: 怒目而視    時間: 2025-3-25 02:50
Introduction,anguage processing, and knowledge-based expert systems. One important dimension of this work is that some of the programs that mimic intelligence are capable of improving at a performance task, and some are not.
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Paul E. Utgofftween measured values of intensity and atmospheric parameters. However, the theoretical basis of the inverse problem solution is well investigated in the case of linear inverse problems only [.]. Thus, to make use of the existing numerical methods the forward model has to be linearized, i.e., a line
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tween measured values of intensity and atmospheric parameters. However, the theoretical basis of the inverse problem solution is well investigated in the case of linear inverse problems only [.]. Thus, to make use of the existing numerical methods the forward model has to be linearized, i.e., a line
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0893-3405 et been observed by the learning program. Learning programs that make undesir- able inductive leaps do so due to undesirable bias. The research problem addressed here is to show how a learning program can learn a desirable inductive bias.978-1-4612-9408-5978-1-4613-2283-2Series ISSN 0893-3405
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