EM algorithm for spike-and-slab priors
Bayesian Inference for Spatio-temporal Spike-and-Slab Priors
... passing algorithm (Sundeep, 2010) for inference in a probabilistic model with ...i.i.d. spike-and-slab priors and a Gaussian ...AMP algorithm is closely related to EP algorithm ...
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Efficient Sparse Bayesian Learning using Spike-and-Slab Priors
... learning algorithm. Our choice in this dissertation is the spike-and-slab prior [58, ...for spike-and-slab priors is dictated by the selective shrinkage effect induced by the ...
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Generalized Spike-and-Slab Priors for Bayesian Group Feature Selection Using Expectation Propagation
... include the reconstruction of medical images (Seeger et al., 2009), the processing of fMRI data (Gerven et al., 2009), the discovery of gene regulators (Hern´andez-Lobato et al., 2008), the pro- cessing of natural ...
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A Truncated EM Approach for Spike-and-Slab Sparse Coding
... on spike-and-slab generalizations of sparse coding (like fully Bayesian ap- proaches), they maintain deterministic approximation procedures for parameter optimiza- ...of spike-and-slab ...
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The Spike-and-Slab Lasso Generalized Linear Models for Prediction and Associated Genes Detection
... the spike-and-slab mixture prior, the shrinkage scale for each predictor can be estimated from the data, yielding weak shrinkage on important predictors, but strong shrinkage on irrelevant predictors, and ...
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A novel automated spike sorting algorithm with adaptable feature extraction
... the EM algorithm approximates the data distribution of a given space, using Gaussian basis ...specific spike event, is sorted into the resulting mixture components based on the probability associated ...
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The spike and slab algorithm
... Step 2 fits a rescaled spike and slab model using only those variables that are not filtered in Step 1. Model fitting is implemented using a Gibbs sampler. Computational times are generally rapid as the ...
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The Spike-and-Slab LASSO
... of spike-and-slab methodology for Bayesian variable selection, its potential for penalized likelihood estimation has largely been ...the Spike-and-Slab LASSO procedure for variable selection ...
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Spike and Slab Dirichlet Process Mixture Models
... Keywords: Spike and Slab; Dirichlet Process; Bayesian Expectation-Maximization (BEM); Mixture ...(DP) priors are used across a wide vari- ety of applications of Bayesian analysis, including Baye- ...
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The EM Algorithm
... The EM algorithm for the hidden MRF is considerably more difficult; see McLachlan (1992, Chapter 13) and the references ...(ICM) algorithm (Besag, 1986), has been adopted for the segmentation of ...
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A Simple Algorithm for Averaging Spike Trains
... the spike train can be largely preserved in a single exemplar like the central spike ...central spike train removes trial-to-trial structure by representing the collection as a single spike ...
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Incremental learning algorithm for spike pattern classification
... complex spike computation tasks including precise time spike sequence generation and spike pattern ...neural spike output matches a desired ...SPAN, Spike Pattern Association Neuron, a ...
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Incorporating Priors for Medical Image Segmentation Using a Genetic Algorithm
... multiple priors for segmentation is the main contribution of this ...genetic algorithm over conventional optimization methods for level set curve ...
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Heuristic Spike Sorting Tuner (HSST), a framework to determine optimal parameter selection for a generic spike sorting algorithm
... the algorithm must accurately estimate these parameters, adding to the complexity of ...K-Means algorithm (MacQueen, 1967) has a single parameter K, which fixes the number of clusters discovered by the ...
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Automated spike sorting algorithm based on Laplacian eigenmaps and k means clustering
... To address the shortcomings of the simulated data set, we have also evaluated the performance of spike sorting algorithms on in-vivo recording from the hippocampus of a freely moving rodent. A surgical procedure ...
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Learning with precise spike times : a new decoding algorithm for liquid state machines
... Poisson spike trains with fre- quency of 20 Hz over interval [0, ...two spike train templates, 100 for each class, of which 50 were used for training and 50 for ...
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An Unsupervised and Drift-Adaptive Spike Detection Algorithm Based on Hybrid Blind Beamforming
... HBBSD algorithm: the SEA algorithm was said to have reached convergence if h ( k +1) − h ( k ) 2 ≤ 10 − 10 ...SEA algorithm used higher-order statistics with p = 2 but switched automatically to p = 3 ...
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Column Capital and Drop Panel Optimization of Flat Slab Using Genetic Algorithm
... Flab slab optimization using genetic algorithm is worked out using various trial error based thickness ...flat slab is initiated mathematically which gives corrolary idea of an angle section with ...
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Column Capital and Drop Panel Optimization of Flat Slab Using Genetic Algorithm
... Flab slab optimization using genetic algorithm is worked out using various trial error based thickness ...flat slab is initiated mathematically which gives corrolary idea of an angle section with ...
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Tutorial on EM Algorithm
... by Arthur P. Dempster, Nan M. Laird, and Donald B. Rubin (Dempster, Laird, & Rubin, 1977). For convenience, let DLR be reference to such three authors. We begin a review of EM algorithm with some basic ...
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