- Realistic neural nets need to learn iconic representations.W. A. Phillips, P. J. B. Hancock & L. S. Smith - 1990 - Behavioral and Brain Sciences 13 (3):505-505.details
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The analysis of the learning needs to be deeper.John E. Rager - 1990 - Behavioral and Brain Sciences 13 (3):505-506.details
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A non-empiricist perspective on learning in layered networks.Michael I. Jordan - 1990 - Behavioral and Brain Sciences 13 (3):497-498.details
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How connectionist models learn: The course of learning in connectionist networks.John K. Kruschke - 1990 - Behavioral and Brain Sciences 13 (3):498-499.details
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Toward a unification of conditioning and cognition in animal learning.William S. Maki - 1990 - Behavioral and Brain Sciences 13 (3):501-502.details
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Analyzing vision at the complexity level: Misplaced complexity?Lester E. Krueger & Chiou-Yueh Tsav - 1990 - Behavioral and Brain Sciences 13 (3):449-450.details
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Probability theory as an alternative to complexity.David G. Lowe - 1990 - Behavioral and Brain Sciences 13 (3):451-452.details
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Support for an intermediate pictorial representation.Michael Mohnhaupt & Bernd Neumann - 1990 - Behavioral and Brain Sciences 13 (3):452-453.details
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Is it really that complex? After all, there are no green elephants.Ralph M. Siegel - 1990 - Behavioral and Brain Sciences 13 (3):453-453.details
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(1 other version)Analyzing vision at the complexity level.John K. Tsotsos - 1990 - Behavioral and Brain Sciences 13 (3):423-445.details
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Advances in neural network theory.Gérard Toulouse - 1990 - Behavioral and Brain Sciences 13 (3):509-509.details
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Are connectionist models just statistical pattern classifiers?Richard M. Golden - 1990 - Behavioral and Brain Sciences 13 (3):494-495.details
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What can psychologists learn from hidden-unit nets?K. Lamberts & G. D'Ydewalle - 1990 - Behavioral and Brain Sciences 13 (3):499-500.details
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A little complexity analysis goes a long way.John K. Tsotsos - 1990 - Behavioral and Brain Sciences 13 (3):458-469.details
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On brains and models.William R. Uttal - 1990 - Behavioral and Brain Sciences 13 (3):456-457.details
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The theory and practice of attention.Kyle R. Cave - 1990 - Behavioral and Brain Sciences 13 (3):445-446.details
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On learnability, empirical foundations, and naturalness.W. J. M. Levelt - 1990 - Behavioral and Brain Sciences 13 (3):501-501.details
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Keeping representations at bay.Stanley Munsat - 1990 - Behavioral and Brain Sciences 13 (3):502-503.details
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Learning from learned networks.M. Pavel - 1990 - Behavioral and Brain Sciences 13 (3):503-504.details
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Connectionist learning and the challenge of real environments.Mark Weaver & Stephen Kaplan - 1990 - Behavioral and Brain Sciences 13 (3):510-511.details
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What connectionists learn: Comparisons of model and neural nets.Bruce Bridgeman - 1990 - Behavioral and Brain Sciences 13 (3):491-492.details
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Representational systems and symbolic systems.Gordon D. A. Brown & Mike Oaksford - 1990 - Behavioral and Brain Sciences 13 (3):492-493.details
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Search and the detection and integration of features.Anne Treisman - 1990 - Behavioral and Brain Sciences 13 (3):454-455.details
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Learning and representation: Tensions at the interface.Steven José Hanson - 1990 - Behavioral and Brain Sciences 13 (3):511-518.details
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But what is the substance of connectionist representation?James Hendler - 1990 - Behavioral and Brain Sciences 13 (3):496-497.details
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Connectionism and classical computation.Nick Chater - 1990 - Behavioral and Brain Sciences 13 (3):493-494.details
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Is unbounded visual search intractable?Andrew Heathcote & D. J. K. Mewhort - 1990 - Behavioral and Brain Sciences 13 (3):449-449.details
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Complexity, guided search, and the data.Jeremy M. Wolfe - 1990 - Behavioral and Brain Sciences 13 (3):457-458.details
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Computation, complexity, and systems in nature.Bradley W. Dickinson - 1990 - Behavioral and Brain Sciences 13 (3):447-447.details
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What are the insights gained train the complexity analysis?Jan-Olof Eklundh - 1990 - Behavioral and Brain Sciences 13 (3):448-449.details
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Problems of extension, representation, and computational irreducibility.Patrick Suppes - 1990 - Behavioral and Brain Sciences 13 (3):507-508.details
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Connectionist models learn what?Timothy van Gelder - 1990 - Behavioral and Brain Sciences 13 (3):509-510.details
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Relatively local neurons in a distributed representation: A neurophysiological perspective.Shabtai Barash - 1990 - Behavioral and Brain Sciences 13 (3):489-491.details
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Expose hidden assumptions in network theory.Karl Haberlandt - 1990 - Behavioral and Brain Sciences 13 (3):495-496.details
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What connectionist models learn: Learning and representation in connectionist networks.Stephen José Hanson & David J. Burr - 1990 - Behavioral and Brain Sciences 13 (3):471-489.details
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There is more to learning then meeth the eye.Noel E. Sharkey - 1990 - Behavioral and Brain Sciences 13 (3):506-507.details
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Adaptation and attention.Steven W. Zucker - 1990 - Behavioral and Brain Sciences 13 (3):458-458.details
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Complexity is complicated.Paul R. Kube - 1990 - Behavioral and Brain Sciences 13 (3):450-451.details
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Algorithmic complexity analysis does not apply to behaving organisms.Gary W. Strong - 1990 - Behavioral and Brain Sciences 13 (3):453-454.details
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Connectionist models: Too little too soon?William Timberlake - 1990 - Behavioral and Brain Sciences 13 (3):508-509.details
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Task-dependent constraints on perceptual architectures.Roy Eagleson - 1990 - Behavioral and Brain Sciences 13 (3):447-448.details
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Approaches to learning and representation.Pat Langley - 1990 - Behavioral and Brain Sciences 13 (3):500-501.details
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Complexity at the neuronal level.Robert Desimone - 1990 - Behavioral and Brain Sciences 13 (3):446-446.details
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Some important constraints on complexity.Leonard Uhr - 1990 - Behavioral and Brain Sciences 13 (3):455-456.details
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