Exemplar Models and Weighted Cue Models in Category Learning

[1]  Geoffrey E. Hinton,et al.  Learning internal representations by error propagation , 1986 .

[2]  D. Medin,et al.  Problem structure and the use of base-rate information from experience. , 1988, Journal of experimental psychology. General.

[3]  W. Estes.  Array models for category learning , 1986, Cognitive Psychology.

[4]  Michael A. Saunders,et al.  Procedures for optimization problems with a mixture of bounds and general linear constraints , 1984, ACM Trans. Math. Softw..

[5]  R. Shepard,et al.  Toward a universal law of generalization for psychological science. , 1987, Science.

[6]  L. Beach.  Recognition, assimilation, and identification of objects. , 1964 .

[7]  J. Kruschke,et al.  ALCOVE: an exemplar-based connectionist model of category learning. , 1992, Psychological review.

[8]  James L. McClelland,et al.  An interactive activation model of context effects in letter perception: I. An account of basic findings. , 1981 .

[9]  Stephen K. Reed,et al.  Pattern recognition and categorization , 1972 .

[10]  G. O. Stone,et al.  An analysis of the delta rule and the learning of statistical associations , 1986 .

[11]  D. Medin,et al.  Linear separability in classification learning. , 1981 .

[12]  G. V. Nakamura.  Knowledge-based classification of ill-defined categories , 1985, Memory & cognition.

[13]  R. Shepard,et al.  Learning and memorization of classifications. , 1961 .

[14]  M. Gluck.  Stimulus Generalization and Representation in Adaptive Network Models of Category Learning , 1991 .

[15]  R. J. Williams,et al.  The logic of activation functions , 1986 .

[16]  Douglas L. Medin,et al.  Context theory of classification learning. , 1978 .

[17]  James L. McClelland,et al.  Nature, nurture, and connections: Implications of connectionist models for cognitive development. , 1991 .

[18]  B. MacWhinney,et al.  Functionalism and the competition model , 1989 .

[19]  B. MacWhinney,et al.  Levels of learning: A comparison of concept formation and language acquisition , 1991 .

[20]  G. Bower,et al.  Evaluating an adaptive network model of human learning , 1988 .

[21]  C. Oden.  Direct, Incremental Learning of Fuzzy Propositions , 1992 .

[22]  R. Taraban,et al.  Language learning: Cues or rules? , 1989 .

[23]  Robert A. Jacobs,et al.  Increased rates of convergence through learning rate adaptation , 1987, Neural Networks.

[24]  L. Beach.  Cue probabilism and inference behavior. , 1964 .

[25]  Roman Taraban,et al.  Category learning in a connectionist model: Learning to decline the German definite article , 1989 .

[26]  D. Massaro.  Some criticisms of connectionist models of human performance , 1988 .

[27]  E. Rosch,et al.  Family resemblances: Studies in the internal structure of categories , 1975, Cognitive Psychology.

[28]  Javier R. Movellan,et al.  Benefits of gain: speeded learning and minimal hidden layers in back-propagation networks , 1991, IEEE Trans. Syst. Man Cybern..

[29]  R. Nosofsky.  American Psychological Association, Inc. Choice, Similarity, and the Context Theory of Classification , 2022 .