What connectionist models learn: Learning and representation in connectionist networks

[1]  G. Shepherd,et al.  Logic operations are properties of computer-simulated interactions between excitable dendritic spines , 1987, Neuroscience.

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

[3]  B. Bridgeman.  Multiplexing in single cells of the alert monkey's visual cortex during brightness discrimination , 1982, Neuropsychologia.

[4]  V. Mountcastle,et al.  Parietal lobe mechanisms for directed visual attention. , 1977, Journal of neurophysiology.

[5]  E. Mark Gold,et al.  Language Identification in the Limit , 1967, Inf. Control..

[6]  Noam Chomsky,et al.  Rules and representations , 1980, Behavioral and Brain Sciences.

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

[8]  Brian Everitt,et al.  Cluster analysis , 1974 .

[9]  B. Bridgeman.  Temporal response characteristics of cells in monkey striate cortex measured with metacontrast masking and brightness discrimination , 1980, Brain Research.

[10]  A. Tversky.  Features of Similarity , 1977 .

[11]  Teuvo Kohonen,et al.  Associative memory. A system-theoretical approach , 1977 .

[12]  Noam Chomsky,et al.  A Review of B. F. Skinner's Verbal Behavior , 1980 .

[13]  Michael I. Jordan,et al.  Task Decomposition Through Competition in a Modular Connectionist Architecture: The What and Where Vision Tasks , 1990, Cogn. Sci..

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

[15]  Pat Langley,et al.  Representational Issues in Learning Systems , 1983, Computer.

[16]  Dean Allemang,et al.  Information processing abstractions: The message still counts more than the medium , 1988, Behavioral and Brain Sciences.

[17]  Robert B. Allen,et al.  Connectionist Language Users , 1990 .

[18]  G. J. Tomko,et al.  Neuronal variability: non-stationary responses to identical visual stimuli. , 1974, Brain research.

[19]  Stierlin.  Organization of Behavior. A Neuropsychological Theory , 1953 .

[20]  David S. Touretzky,et al.  A Computational Basis for Phonology , 1989, NIPS.

[21]  J. Nadal,et al.  Learning in feedforward layered networks: the tiling algorithm , 1989 .

[22]  James L. McClelland,et al.  James L. McClelland, David Rumelhart and the PDP Research Group, Parallel distributed processing: explorations in the microstructure of cognition . Vol. 1. Foundations . Vol. 2. Psychological and biological models . Cambridge MA: M.I.T. Press, 1987. , 1989, Journal of Child Language.

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

[24]  Eric B. Baum,et al.  A Proposal for More Powerful Learning Algorithms , 1989, Neural Computation.

[25]  W. Köhler.  The Mentality of Apes. , 2018, Nature.

[26]  David J. Burr,et al.  Experiments on neural net recognition of spoken and written text , 1988, IEEE Trans. Acoust. Speech Signal Process..

[27]  R. Shepard.  The analysis of proximities: Multidimensional scaling with an unknown distance function. II , 1962 .

[28]  James A. Hendler,et al.  Marker‐passing over Microfeatures: Towards a Hybrid Symbolic/Connectionist Model , 1989 .

[29]  Noam Chomsky.  Review of B.F. Skinner, Verbal Behavior , 1959 .

[30]  Roger N. Shepard,et al.  How fully should connectionism be activated? Two sources of excitation and one of inhibition , 1988, Behavioral and Brain Sciences.

[31]  Barak A. Pearlmutter.  Learning state space trajectories in recurrent neural networks : a preliminary report. , 1988 .

[32]  Donald F. Specht,et al.  Generation of Polynomial Discriminant Functions for Pattern Recognition , 1967, IEEE Trans. Electron. Comput..

[33]  James L. McClelland,et al.  Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .

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

[35]  Jerome A. Feldman,et al.  Connectionist Models and Their Applications: Introduction , 1985 .

[36]  J. Hyvärinen,et al.  Function of the parietal associative area 7 as revealed from cellular discharges in alert monkeys. , 1974, Brain : a journal of neurology.

[37]  Zenon W. Pylyshyn,et al.  What the Mind’s Eye Tells the Mind’s Brain: A Critique of Mental Imagery , 1973 .

[38]  Gèunther Palm,et al.  Neural Assemblies: An Alternative Approach to Artificial Intelligence , 1982 .

[39]  R. Andersen,et al.  Callosal and prefrontal associational projecting cell populations in area 7A of the macaque monkey: A study using retrogradely transported fluorescent dyes , 1985, The Journal of comparative neurology.

[40]  V. Braitenberg.  Reading the structure of brains , 1990 .

[41]  S. M. Carroll,et al.  Construction of neural nets using the radon transform , 1989, International 1989 Joint Conference on Neural Networks.

[42]  V. Mountcastle,et al.  Visual input to the visuomotor mechanisms of the monkey's parietal lobe. , 1977, Science.

[43]  D. Rumelhart,et al.  Philosophy and Connectionist Theory , 1991 .

[44]  Douglas R. Hofstadter,et al.  Common sense and conceptual halos , 1988, Behavioral and Brain Sciences.

[45]  P. Langley,et al.  Production system models of learning and development , 1987 .

[46]  W. A. Phillips.  On the distinction between sensory storage and short-term visual memory , 1974 .

[47]  G. Hartmann,et al.  Parallel Processing in Neural Systems and Computers , 1990 .

[48]  W. Estes,et al.  Base-rate effects in category learning: a comparison of parallel network and memory storage-retrieval models. , 1989, Journal of experimental psychology. Learning, memory, and cognition.

[49]  E. Kehoe,et al.  Temporal primacy overrides prior training in serial compound conditioning of the rabbit’s nictitating membrane response , 1987 .

[50]  Robert S. Epstein.  Representation: A concept that fills no gaps , 1982, Behavioral and Brain Sciences.

[51]  Idan Segev,et al.  Methods in Neuronal Modeling , 1988 .

[52]  M. Sidman,et al.  Conditional discrimination vs. matching to sample: an expansion of the testing paradigm. , 1982, Journal of the experimental analysis of behavior.

[53]  Pineda,et al.  Generalization of back-propagation to recurrent neural networks. , 1987, Physical review letters.

[54]  Yoshiro Miyata,et al.  The learning and planning of actions , 1988 .

[55]  R Ratcliff,et al.  Connectionist models of recognition memory: constraints imposed by learning and forgetting functions. , 1990, Psychological review.

[56]  J. Gibson.  The Senses Considered As Perceptual Systems , 1967 .

[57]  B. Bridgeman,et al.  The physiology of attention: participation of cat striate cortex in behavioral choice , 1989, Psychological research.

[58]  H. Roitblat.  The meaning of representation in animal memory , 1982, Behavioral and Brain Sciences.

[59]  B. Skinner,et al.  Science and human behavior , 1953 .

[60]  Richard O. Duda,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[61]  James S. Albus,et al.  New Approach to Manipulator Control: The Cerebellar Model Articulation Controller (CMAC)1 , 1975 .

[62]  Geoffrey E. Hinton,et al.  A Learning Algorithm for Boltzmann Machines , 1985, Cogn. Sci..

[63]  Pat Langley,et al.  A computational theory of motor learning , 1987, Comput. Intell..

[64]  W. Levelt.  Formal grammars in linguistics and psycholinguistics : Vol.III, Psycholinguistic applications , 1974 .

[65]  V. Braitenberg.  Vehicles, Experiments in Synthetic Psychology , 1984 .

[66]  T. Zentall,et al.  Memory codes in pigeon short-term memory: Effects of varying the number of sample and comparison stimuli☆ , 1987 .

[67]  John W. Tukey,et al.  Exploratory Data Analysis. , 1979 .

[68]  L. Nadel.  Some thoughts on the proper foundations for the study of cognition in animals , 1982, Behavioral and Brain Sciences.

[69]  M. A. Gluck,et al.  A Configural-Cue Network Model of Classification Learning , 1988 .

[70]  Terrence J. Sejnowski,et al.  NETtalk: a parallel network that learns to read aloud , 1988 .

[71]  Allen Newell,et al.  Computer science as empirical inquiry: symbols and search , 1976, CACM.

[72]  Leslie G. Valiant,et al.  A theory of the learnable , 1984, STOC '84.

[73]  Kehoe Ej.  Connectionist models of conditioning: A tutorial. , 1989 .

[74]  G. Edelman.  Neural Darwinism: The Theory Of Neuronal Group Selection , 1989 .

[75]  George Cybenko,et al.  Approximation by superpositions of a sigmoidal function , 1992, Math. Control. Signals Syst..

[76]  Stephen A. Ritz,et al.  Distinctive features, categorical perception, and probability learning: some applications of a neural model , 1977 .

[77]  S. Pinker,et al.  On language and connectionism: Analysis of a parallel distributed processing model of language acquisition , 1988, Cognition.

[78]  D. Lightfoot.  The child's trigger experience: Degree-0 learnability , 1989, Behavioral and Brain Sciences.

[79]  Stephen Grossberg,et al.  Competitive Learning: From Interactive Activation to Adaptive Resonance , 1987, Cogn. Sci..

[80]  T. Bever,et al.  The relation between linguistic structure and associative theories of language learning—A constructive critique of some connectionist learning models , 1988, Cognition.

[81]  James L. McClelland,et al.  Parallel Distributed Processing: Explorations in the Microstructure of Cognition : Psychological and Biological Models , 1986 .

[82]  Richard A. Andersen,et al.  Value, variable, and coarse coding by posterior parietal neurons , 1986, Behavioral and Brain Sciences.

[83]  Zenon W. Pylyshyn,et al.  Computation and Cognition: Toward a Foundation for Cognitive Science , 1984 .

[84]  R. Shepard,et al.  A nonmetric variety of linear factor analysis , 1974 .

[85]  H. Gardner,et al.  The Mind's New Science , 1985 .

[86]  Tim van Gelder,et al.  Compositionality: A Connectionist Variation on a Classical Theme , 1990, Cogn. Sci..

[87]  David C. Palmer,et al.  THE INTERPRETATION OF COMPLEX HUMAN BEHAVIOR: SOME REACTIONS TO PARALLEL DISTRIBUTED PROCESSING, EDITED BY J. L. McCLELLAND, D. E. RUMELHART, AND THE PDP RESEARCH GROUP1 , 1989 .

[88]  Thomas M. Cover,et al.  Geometrical and Statistical Properties of Systems of Linear Inequalities with Applications in Pattern Recognition , 1965, IEEE Trans. Electron. Comput..

[89]  A. Logue.  Cognitive psychology's representation of behaviorism , 1982, Behavioral and Brain Sciences.

[90]  E. Kehoe.  A layered network model of associative learning: learning to learn and configuration. , 1988, Psychological review.

[91]  A G Barto,et al.  Toward a modern theory of adaptive networks: expectation and prediction. , 1981, Psychological review.

[92]  Geoffrey E. Hinton,et al.  Learning representations by back-propagating errors , 1986, Nature.

[93]  John R. Anderson.  The Architecture of Cognition , 1983 .

[94]  Robert O. Winder,et al.  Threshold logic , 1971, IEEE Spectrum.

[95]  G. W. Strong,et al.  A solution to the tag-assignment problem for neural networks , 1989, Behavioral and Brain Sciences.

[96]  Terrence J. Sejnowski,et al.  Learned classification of sonar targets using a massively parallel network , 1988, IEEE Trans. Acoust. Speech Signal Process..

[97]  John A. Hartigan,et al.  Clustering Algorithms , 1975 .

[98]  D. Willshaw,et al.  Theories of associative recall , 1970, Quarterly Reviews of Biophysics.

[99]  W. Pitts,et al.  A Logical Calculus of the Ideas Immanent in Nervous Activity (1943) , 2021, Ideas That Created the Future.

[100]  James L. McClelland,et al.  Explorations in parallel distributed processing: a handbook of models, programs, and exercises , 1988 .

[101]  Terrence J. Sejnowski,et al.  Network model of shape-from-shading: neural function arises from both receptive and projective fields , 1988, Nature.

[102]  S. Pinker,et al.  Connections and symbols , 1988 .

[103]  Paul E. Utgoff,et al.  Machine Learning of Inductive Bias , 1986 .

[104]  John R. Searle,et al.  Minds, brains, and programs , 1980, Behavioral and Brain Sciences.

[105]  L. N. Kanal,et al.  Uncertainty in Artificial Intelligence 5 , 1990 .

[106]  Jerome A. Feldman,et al.  Connectionist Models and Their Properties , 1982, Cogn. Sci..

[107]  Allen Newell,et al.  Towards Chunking as a General Learning Mechanism , 1984, AAAI.

[108]  Ronald J. Williams,et al.  A Learning Algorithm for Continually Running Fully Recurrent Neural Networks , 1989, Neural Computation.

[109]  Geoffrey E. Hinton,et al.  Parallel Models of Associative Memory , 1989 .

[110]  Marvin Minsky,et al.  Computation : finite and infinite machines , 2016 .

[111]  Balas K. Natarajan,et al.  On learning Boolean functions , 1987, STOC.

[112]  Douglas B. Lenat,et al.  Why AM and EURISKO Appear to Work , 1984, Artif. Intell..

[113]  Nils J. Nilsson,et al.  Learning Machines: Foundations of Trainable Pattern-Classifying Systems , 1965 .

[114]  N. Chater,et al.  Autonomy, implementation and cognitive architecture: A reply to Fodor and Pylyshyn , 1990, Cognition.

[115]  P. Culicover,et al.  Neural connections, mental computation , 1988 .

[116]  J. Elman.  Representation and structure in connectionist models , 1991 .

[117]  D. Robinson,et al.  Parietal association cortex in the primate: sensory mechanisms and behavioral modulations. , 1978, Journal of neurophysiology.

[118]  Paul W. Cooper,et al.  The Hypersphere in Pattern Recognition , 1962, Inf. Control..

[119]  David E. Rumelhart,et al.  Product Units: A Computationally Powerful and Biologically Plausible Extension to Backpropagation Networks , 1989, Neural Computation.

[120]  James L. McClelland,et al.  A distributed, developmental model of word recognition and naming. , 1989, Psychological review.

[121]  J. Stephen Judd,et al.  On the complexity of loading shallow neural networks , 1988, J. Complex..

[122]  R. Pfeifer,et al.  Connectionism in Perspective , 1989 .

[123]  E. Rosch,et al.  Structural bases of typicality effects. , 1976 .

[124]  Christoph von der Malsburg,et al.  Pattern recognition by labeled graph matching , 1988, Neural Networks.

[125]  Teuvo Kohonen,et al.  Self-Organization and Associative Memory , 1988 .

[126]  Noam Chomsky.  Knowledge of language: its nature, origin, and use , 1988 .

[127]  E. Hilgard,et al.  Theories of Learning , 1981 .

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

[129]  Karl H. Pribram,et al.  The Languages of the Brain , 2002 .

[130]  James L. McClelland,et al.  Distributed memory and the representation of general and specific information. , 1985, Journal of experimental psychology. General.