[PDF] Top 20 Nonlinear Models Using Dirichlet Process Mixtures
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Nonlinear Models Using Dirichlet Process Mixtures
... In the protein fold prediction problem discussed in this paper, classes were regarded as a set of unrelated entities. However, these classes are not completely unrelated, and can be grouped into four major structural ... See full document
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On Bayesian Estimation of Dirichlet Process Lognormal Mixture Models and Comparison of Treatments in Censoring
... related Dirichlet process (DP) prior distribution for estimating patient ...(K-M) models used to estimate survival to establish model ...these models is also ...resulting Dirichlet ... See full document
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Improving Prediction from Dirichlet Process Mixtures via Enrichment
... conditional models can approximate a wide range of response distributions that may change flexibly with the ...conditional models based on dependent ... See full document
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Improving prediction from Dirichlet process mixtures via enrichment
... conditional models can approximate a wide range of response distributions that may change flexibly with the ...conditional models based on dependent ... See full document
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Modeling and visualizing uncertainty in gene expression clusters using Dirichlet process mixtures
... Gaussian mixtures (or Dirichlet process mixtures, DPM) [5], ...a Dirichlet process prior [5], [6], ...mixture models efficiently using Markov chain Monte Carlo ... See full document
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Mixtures of Nonlinear Poisson Autoregressions
... consider models for count time series, which allow for the mean process to change according to the values of an unobservable discrete random ...the process of infected cases ...properly models ... See full document
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Dirichlet Process Mixture Models For Markov Processes
... Markov process (refer to Appendix A for the definition) under the assumption that both the transition density and the density for the invariant distribution are uniformly ...Mixture models are flexible ... See full document
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Dirichlet Process Mixtures of Generalized Linear Models
... N(−3, 2)) to place greater emphasis on response fit. The non-conjugate parameters were updated using the Hamiltonian dynamics method of Neal (2010). Hyperparameters were chosen based on performance on a subset of ... See full document
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Sensor based human activity mining using Dirichlet process mixtures of directional statistical models
... the sampler is set as 1; i.e. all the data are from one cluster. Each chain runs 200 iterations. The reported Ks are the mean of the 10 modes of the ten chains and NMIs are the average of the ten runs with the first half ... See full document
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Classification with Incomplete Data Using Dirichlet Process Priors
... The Dirichlet process (Ferguson, 1973) has been an active topic in many applications since the middle 1990s, for example, density estimation (Escobar and West, 1995; MacEachern and M¨uller, 1998; Dunson et ... See full document
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TSDPMM: Incorporating Prior Topic Knowledge into Dirichlet Process Mixture Models for Text Clustering
... would like to focus on. Clearly, these prior topic- s can be represented as sets of words, which are available in many real-world applications. They can serve as weakly supervised information to en- hance the ... See full document
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Beating-Time Gestures Imitation Learning for Humanoid Robots
... conducting models into beating-time ...conducting models were defined upfront. The definition and selection of models was done in collaboration with the ...five models. The assignment of ... See full document
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Posterior convergence rates of dirichlet mixtures at smooth densities
... super-smooth mixtures can be well ap- proximated by finite normal mixtures with a small number of components ...finite-dimensional models) with a nearly parametric convergence rate as a ...mal ... See full document
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Nonlinearity In Exchange Rates and Forecasting
... structural models have not been able to explain the high level of volatility which exists in these ...the models focusing on market fundamentals are able to provide good explanations of the movements in the ... See full document
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Bayesian Inference on a Cox Process Associated with a Dirichlet Process
... Cox process associated with a Dirichlet process was proposed with an emphasis on modeling spatial distri- butions of events generated by hidden ...a Dirichlet process centered on a ... See full document
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Update Summarization using a Multi level Hierarchical Dirichlet Process Model
... HDP models, the sentence level is disregarded and we cannot directly get the aspect distribution of ...Latent Dirichlet Allocation (LDA) models (Chemudugunta et ...introduces Dirichlet ... See full document
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Dirichlet series and approximate analytical solutions of MHD flow over a linearly stretching sheet
... sheet using this approach and found more ac- curate solution compared with earlier numerical ...sheet using these methods and found more accurate results compared with the classical numerical ...present ... See full document
8
Ion Channels are Biological Devices
... Power Supply = spatially nonuniform inhomogeneous Dirichlet Boundary Conditions Flows,. Non-ideal mixtures including Ca 2+.[r] ... See full document
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Existence of solutions to nonlinear fractional differential equations with boundary conditions on an infinite interval in Banach spaces
... in a real Banach space. Nyamoradi et al. [] considered an infinite fractional boundary value problem for singular integro-differential equation of mixed type on the half-line. Liu et al. [] established sufficient ... See full document
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An H1 Galerkin method for a Stefan problem with a quasilinear parabolic equation in non divergence form
... A Galerkin Method For a Single Phase Nonlinear Stefan Problem with Dirichlet Boundary Conditions, Submitted.. Free-Boundary Problems For Nonlinear Parabolic Equations With Nonlinear Free[r] ... See full document
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