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An Adaptive Sequential Monte Carlo Algorithm for Computing Permanents
Sequential Monte Carlo Permanents Relative Variance
2013/6/14
We consider the computation of the permanent of a binary n by n matrix. It is well- known that the exact computation is a #P complete problem. A variety of Markov chain Monte Carlo (MCMC) computationa...
Characterizing A Database of Sequential Behaviors with Latent Dirichlet Hidden Markov Models
LDHMMs sequential data variational inference variational EM behavior modeling sequence classification
2013/6/14
This paper proposes a generative model, the latent Dirichlet hidden Markov models (LDHMM), for characterizing a database of sequential behaviors (sequences). LDHMMs posit that each sequence is generat...
Matching on-the-fly in Sequential Experiments for Higher Power and Efficiency
Matching on-the-fly in Sequential Experiments Higher Power Efficiency
2013/6/14
We propose a dynamic allocation procedure that increases power and efficiency when measuring an average treatment effect in sequential randomized trials. Subjects arrive iteratively and are either ran...
Bayesian Multi-Dipole Modeling of Single MEG Topographies by Adaptive Sequential Monte Carlo Samplers
Magnetoencephalography inverse problem Multi-object estimation Multi-dipole models Adaptive Sequential Monte Carlo samplers
2013/6/14
We describe a novel Bayesian approach to the estimation of neural currents from a single distribution of magnetic field, measured by magnetoencephalography. We model neural currents as an unknown numb...
Sequential testing over multiple stages and performance analysis of data fusion
Sequential testing over multiple stages performance analysis data fusion
2013/4/28
We describe a methodology for modeling the performance of decision-level data fusion between different sensor configurations, implemented as part of the JIEDDO Analytic Decision Engine (JADE). We firs...
Generalized Thompson Sampling for Sequential Decision-Making and Causal Inference
Generalized Thompson Sampling Sequential Decision-Making Causal Inference
2013/5/2
Recently, it has been shown how sampling actions from the predictive distribution over the optimal action-sometimes called Thompson sampling-can be applied to solve sequential adaptive control problem...
Towards Automatic Model Comparison: An Adaptive Sequential Monte Carlo Approach
Adaptive Monte Carlo algorithms Bayesian model comparison Normalising constants Path sampling Thermodynamic integration
2013/4/27
Model comparison for the purposes of selection, averaging and validation is a problem found throughout statistics and related disciplines. Within the Bayesian paradigm, these problems all require the ...
Sequential Estimation Methods from Inclusion Principle
Sequential Estimation Methods Inclusion Principle
2012/9/17
In this paper, we propose new sequential estimation methodsbased on inclusion principle. The main idea is to reformulate the estimation problems as constructing sequential random intervals and use con...
Sequential multi-sensor change-point detection
Sequential multi-sensor change-point detection
2012/9/19
We develop a mixture procedure for monitoring parallel streams of data for a change-point that affects only a subset of them, without assuming a spatial structure relating the data streams to one anot...
Sequential detection of multiple change points in networks: a graphical model approach
Sequential detection of multiple change points in networks graphical model approach
2012/9/19
We propose a probabilistic formulation that enables sequential detection of multiple change points in a network setting. We present a class of sequential detection rules for cer-tain functionals of ch...
Efficient Estimators for Sequential and Resolution-Limited Inverse Problems
deconvolution ill-posed image processing sig-nal recovery
2012/9/18
A common problem in the sciences is that a signal of interest is observed only indirectly, through smooth functionals of the signal whose values are then obscured by noise. In suchinverse problems, th...
Sequential Lasso for feature selection with ultra-high dimensional feature space
extended BIC feature selection selection consistency Sequential Lasso
2011/7/19
We propose a novel approach, Sequential Lasso, for feature selection in linear regression models with ultra-high dimensional feature spaces.
Sequential Monte Carlo EM for multivariate probit models
Maximum likelihood Multivariate probit Monte Carlo EM adaptive sequential Monte Carlo
2011/7/19
A Monte Carlo EM algorithm is considered for the maximum likelihood estimation of multivariate probit models.
Censored Truncated Sequential Spectrum Sensing for Cognitive Radio Networks
Censored Truncated Sequential Spectrum Sensing Cognitive Radio Networks
2011/7/6
Reliable spectrum sensing is a key functionality of a cognitive radio network. Cooperative spectrum sensing improves the detection reliability of a cognitive radio system but also increases the system...
Sequential estimation for covariate-adjusted response-adaptive designs
Covariate-adjustment logistic regression response-adaptive design se-quential estimation
2011/7/6
In clinical trials, a covariate-adjusted response-adaptive (CARA) design allows a subject newly entering a trial a better chance of being allocated to a superior treatment regimen based on cumulative ...