Hierarchical mixtures of experts and the EM algorithm

Authors:
Michael I. Jordan;Robert A. Jacobs
Affiliations:
-;-
Venue:
Neural Computation
Year:
1994

Citing 0
Cited 349

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Mixture of random prototype-based local experts

HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part I
Application of mixture of experts to construct real estate appraisal models

HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part I
A review and comparison of strategies for multi-step ahead time series forecasting based on the NN5 forecasting competition

Expert Systems with Applications: An International Journal
Efficient margin-based rank learning algorithms for information retrieval

CIVR'06 Proceedings of the 5th international conference on Image and Video Retrieval
Multi-module image classification system

FQAS'06 Proceedings of the 7th international conference on Flexible Query Answering Systems
Time-frequency distributions in the classification of epilepsy from EEG signals

Expert Systems with Applications: An International Journal
Identification of piecewise affine systems based on statistical clustering technique

Automatica (Journal of IFAC)
Eye movements as time-series random variables: A stochastic model of eye movement control in reading

Cognitive Systems Research
New specifics for a hierarchial estimator meta-algorithm

ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part II
Measurement and the explanation of adaptive and novel behaviors in real and artificial creatures

Cognitive Systems Research
Stochastic approximation learning for mixtures of multivariate elliptical distributions

Neurocomputing
Neural expert networks for faster combined collaborative and content-based recommendation

Journal of Computational Methods in Sciences and Engineering
Discriminative clustering for market segmentation

Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
A mixture of experts approach to multi-strategy image quality assessment

ICIAR'12 Proceedings of the 9th international conference on Image Analysis and Recognition - Volume Part I
Designing Model Based Classifiers by Emphasizing Soft Targets

Fundamenta Informaticae - Advances in Artificial Intelligence and Applications
Solving inverse problems by decomposition, classification and simple modeling

Information Sciences: an International Journal
Combining classifiers under probabilistic models: experimental comparative analysis of methods

Expert Systems: The Journal of Knowledge Engineering
On convergence rates of mixtures of polynomial experts

Neural Computation
Local expert forest of score fusion for video event classification

ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
Detection of distributed denial of service attacks using an ensemble of adaptive and hybrid neuro-fuzzy systems

Computer Communications
A model-learner pattern for bayesian reasoning

POPL '13 Proceedings of the 40th annual ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Ensemble classifier generation using non-uniform layered clustering and Genetic Algorithm

Knowledge-Based Systems
Investigation of mixture of experts applied to residential premises valuation

ACIIDS'13 Proceedings of the 5th Asian conference on Intelligent Information and Database Systems - Volume Part II
Multi-modal convergence maps: from body schema and self-representation to mental imagery

Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Classification model for detecting and managing credit loan fraud based on individual-level utility concept

ACM SIGMIS Database
Time-dependent series variance learning with recurrent mixture density networks

Neurocomputing
Online learning of single-and multivalued functions with an infinite mixture of linear experts

Neural Computation
Online expectation maximization for reinforcement learning in POMDPs

IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
A multi-objective evolutionary algorithm-based ensemble optimizer for feature selection and classification with neural network models

Neurocomputing
Mixtures of Gaussian process models for human pose estimation

Image and Vision Computing
Robust mixture regression using the t-distribution

Computational Statistics & Data Analysis
Mixtures of experts for understanding model discrepancy in dynamic computer models

Computational Statistics & Data Analysis
Constrained Multilevel Latent Class Models for the Analysis of Three-Way Three-Mode Binary Data

Journal of Classification
Learning to resize image

Neurocomputing
Embedded local feature selection within mixture of experts

Information Sciences: an International Journal

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Abstract

We present a tree-structured architecture for supervisedlearning. The statistical model underlying the architecture is ahierarchical mixture model in which both the mixture coefficientsand the mixture components are generalized linear models (GLIM's).Learning is treated as a maximum likelihood problem; in particular,we present an Expectation-Maximization (EM) algorithm for adjustingthe parameters of the architecture. We also develop an on-linelearning algorithm in which the parameters are updatedincrementally. Comparative simulation results are presented in therobot dynamics domain.