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Machine learning approaches: from theory to application in schizophreniaAn examination of the language construct in NIMH's research domain criteria: Time for reconceptualization!Statistical coding and decoding of heartbeat intervalsModel averaging, optimal inference, and habit formation.Generating highly accurate prediction hypotheses through collaborative ensemble learning.Spatiotemporal features for asynchronous event-based data.A classification paradigm for distributed vertically partitioned data.A review of ensemble methods for de novo motif discovery in ChIP-Seq data.A Novel Approach Based on Data Redundancy for Feature Extraction of EEG Signals.Estimating the relevance of world disturbances to explain savings, interference and long-term motor adaptation effects.Boosting regression estimators.Topological mappings of video and audio data.The MEE principle in data classification: a perceptron-based analysis.Electrophysiological responses to feedback during the application of abstract rules.Quasi-linear score for capturing heterogeneous structure in biomarkers.Learning not to generalize: modular adaptation of visuomotor gain.A neurodynamic account of spontaneous behaviourImproving ECG classification accuracy using an ensemble of neural network modules.Modelling individual differences in the form of Pavlovian conditioned approach responses: a dual learning systems approach with factored representations.Mechanisms of hierarchical reinforcement learning in corticostriatal circuits 1: computational analysis.Interpretable per case weighted ensemble method for cancer associations.Unsupervised Learning in an Ensemble of Spiking Neural Networks Mediated by ITDP.Why Are There Failures of Systematicity? The Empirical Costs and Benefits of Inducing Universal Constructions.Reversal Learning in Humans and Gerbils: Dynamic Control Network Facilitates Learning.Anatomical and functional plasticity in early blind individuals and the mixture of experts architecture.A rational model of function learning.Toward cognitive pipelines of medical assistance algorithms.Mechanisms for Robust Cognition.Clustering high-dimensional mixed data to uncover sub-phenotypes: joint analysis of phenotypic and genotypic data.Strategy selection: An introduction to the modeling challenge.A Universal Approximation Theorem for Mixture-of-Experts Models.Mapping behavioral landscapes for animal movement: a finite mixture modeling approach.Methods for combining experts' probability assessments.Democratic integration: self-organized integration of adaptive cues.Active lead-in variability affects motor memory formation and slows motor learning.Evolving a Behavioral Repertoire for a Walking Robot.Modeling Search Behaviors during the Acquisition of Expertise in a Sequential Decision-Making Task.Multivariate bernoulli mixture models with application to postmortem tissue studies in schizophrenia.Soft mixer assignment in a hierarchical generative model of natural scene statistics.The importance of physicochemical characteristics and nonlinear classifiers in determining HIV-1 protease specificity.
P2860
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P2860
description
article
@en
wetenschappelijk artikel
@nl
наукова стаття, опублікована в лютому 1991
@uk
ലേഖനം
@ml
name
Adaptive Mixtures of Local Experts
@en
Adaptive Mixtures of Local Experts
@nl
type
label
Adaptive Mixtures of Local Experts
@en
Adaptive Mixtures of Local Experts
@nl
prefLabel
Adaptive Mixtures of Local Experts
@en
Adaptive Mixtures of Local Experts
@nl
P2093
P356
P1433
P1476
Adaptive Mixtures of Local Experts
@en
P2093
Geoffrey E Hinton
Michael I Jordan
Robert A Jacobs
Steven J Nowlan
P356
10.1162/NECO.1991.3.1.79
P577
1991-01-01T00:00:00Z