On-Line Expectation–Maximization Algorithm for latent Data Models
From MaRDI portal
Publication:2920258
DOI10.1111/j.1467-9868.2009.00698.xzbMath1250.62015arXiv0712.4273OpenAlexW1686266550MaRDI QIDQ2920258
Publication date: 25 October 2012
Published in: Journal of the Royal Statistical Society Series B: Statistical Methodology (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/0712.4273
stochastic approximationadaptive algorithmson-line estimationmixture of regressionsPolyak-Ruppert averaging
Lua error in Module:PublicationMSCList at line 37: attempt to index local 'msc_result' (a nil value).
Related Items (45)
Dynamic Stochastic Blockmodel Regression for Network Data: Application to International Militarized Conflicts ⋮ An online expectation maximization algorithm for exploring general structure in massive networks ⋮ Inertial stochastic PALM and applications in machine learning ⋮ Online multi-label dependency topic models for text classification ⋮ Online EM for functional data ⋮ Estimating random-intercept models on data streams ⋮ Online algorithm for variance components estimation ⋮ Model-based clustering of high-dimensional data streams with online mixture of probabilistic PCA ⋮ Online Learning with (Multiple) Kernels: A Review ⋮ Compressive statistical learning with random feature moments ⋮ Latent tree models for hierarchical topic detection ⋮ Nonparametric estimation of multivariate elliptic densities via finite mixture sieves ⋮ Global implicit function theorems and the online expectation–maximisation algorithm ⋮ Multivariate online regression analysis with heterogeneous streaming data ⋮ Adaptive sequential Monte Carlo by means of mixture of experts ⋮ A Clustered Gaussian Process Model for Computer Experiments ⋮ Recursive parameter estimation algorithm of the Dirichlet hidden Markov model ⋮ Graph prototypical contrastive learning ⋮ Mini-batch learning of exponential family finite mixture models ⋮ Divide-and-conquer Bayesian inference in hidden Markov models ⋮ Stochastic variable metric proximal gradient with variance reduction for non-convex composite optimization ⋮ The limited-memory recursive variational Gaussian approximation (L-RVGA) ⋮ Doubly-online changepoint detection for monitoring health status during sports activities ⋮ Efficient inference in state-space models through adaptive learning in online Monte Carlo expectation maximization ⋮ Online expectation maximization based algorithms for inference in hidden Markov models ⋮ Properties of the stochastic approximation EM algorithm with mini-batch sampling ⋮ Emergence of Optimal Decoding of Population Codes Through STDP ⋮ Online Learning of Single- and Multivalued Functions with an Infinite Mixture of Linear Experts ⋮ Stochastic Multichannel Ranking with Brain Dynamics Preferences ⋮ Bayesian Inference and Online Learning in Poisson Neuronal Networks ⋮ Statistical models for deformable templates in image and shape analysis ⋮ Robust identification of linear ARX models with recursive EM algorithm based on Student's t-distribution ⋮ Posterior Weighted Reinforcement Learning with State Uncertainty ⋮ On-line EM variants for multivariate normal mixture model in background learning and moving foreground detection ⋮ Recursive online EM estimation of mixture autoregressions ⋮ Scalable estimation strategies based on stochastic approximations: classical results and new insights ⋮ Stream-suitable optimization algorithms for some soft-margin support vector machine variants ⋮ Fast incremental expectation maximization for finite-sum optimization: nonasymptotic convergence ⋮ An Asynchronous Distributed Expectation Maximization Algorithm for Massive Data: The DEM Algorithm ⋮ Summary statistics and discrepancy measures for approximate Bayesian computation via surrogate posteriors ⋮ Estimating multilevel models on data streams ⋮ Online identification of time‐delay jump Markov autoregressive exogenous systems with recursive expectation‐maximization algorithm ⋮ Simulation of foraging behavior using a decision-making agent with Bayesian and inverse Bayesian inference: temporal correlations and power laws in displacement patterns ⋮ Unnamed Item ⋮ On particle methods for parameter estimation in state-space models
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Convergence rate and averaging of nonlinear two-time-scale stochastic approximation algo\-rithms
- Almost sure convergence of Titterington's recursive estimator for mixture models
- On the convergence properties of the EM algorithm
- New method of stochastic approximation type
- Weak convergence rates for stochastic approximation with application to multiple targets and simulated annealing
- Stochastic approximation and its applications
- Online EM algorithm for mixture with application to Internet traffic modeling
- Acceleration of Stochastic Approximation by Averaging
- Stability of Stochastic Approximation under Verifiable Conditions
- Recursive EM and SAGE-inspired algorithms with application to DOA estimation
- Tools for statistical inference. Methods for the exploration of posterior distributions and likelihood functions.
This page was built for publication: On-Line Expectation–Maximization Algorithm for latent Data Models