yusuke1997/dblp-id-title huggingface dataset:
Multivariate generalized linear mixed models with semi-nonparametric and smooth nonparametric random effects densities
A new resampling method for meta Gaussian distributions
Likelihood-based and Bayesian methods for Tweedie compound Poisson linear mixed models
Heavy Lasso: sparse penalized regression under heavy-tailed noise via data-augmented soft-thresholding
Estimation of the Additive Hazards Model Based on Interval-censored Failure Time Data with Random Change Point
Estimation across multiple models with application to Bayesian computing and software development
High-dimensional changepoint detection via a geometrically inspired mapping
Acceleration of the Multiple-Try Metropolis algorithm using antithetic and stratified sampling
Comparing change-point location in independent series
Efficient Likelihood-Based Temporal Changepoint Detection in Spatio-Temporal Processes
Parallel Selected Inversion for Space-Time Gaussian Markov Random Fields
Maximum likelihood estimation of the Weibull distribution with reduced bias
Manifold-constrained Gaussian process inference for time-varying parameters in dynamic systems
Penalised spline estimation for generalised partially linear single-index models
Using intersection matrices to identify graphical structure
Spline estimation of functional principal components via manifold conjugate gradient algorithm
The exact distribution of the maximum, minimum and the range of Multinomial/Dirichlet and Multivariate Hypergeometric frequencies
Separating trend and cyclical dynamics in state space models with exogenous inputs
Using prior-data conflict to tune Bayesian regularized regression models
Laplace based Bayesian inference for ordinary differential equation models using regularized artificial neural networks
Algorithmic parameterization of mixed treatment comparisons
Locally sparse and robust partial least squares in scalar-on-function regression
Trans-cGAN: transformer-Unet-based generative adversarial networks for cross-modality magnetic resonance image synthesis
Unbalanced distributed estimation and inference for the precision matrix in Gaussian graphical models
Regularized Gaussian belief propagation
Non-local spatially varying finite mixture models for image segmentation
Have I seen you before? Principles of Bayesian predictive classification revisited
A breakpoint detection in the mean model with heterogeneous variance on fixed time intervals
Parametric bootstrap goodness-of-fit testing for Wehrly-Johnson bivariate circular distributions
Learning causal structure from mixed data with missing values using Gaussian copula models
Bayesian nonparametric priors for hidden Markov random fields
An Online Updating Approach for Estimating and Testing Mediation Effects with Big Data Streams
Sparse logistic functional principal component analysis for binary data
Design of computer experiments: space filling and beyond
Simultaneous estimation for non-crossing multiple quantile regression with right censored data
Exact simulation of normal tempered stable processes of OU type with applications
Uncertainty Quantification in Bayesian Reduced-Rank Sparse Regressions
A sparse PAC-Bayesian approach for high-dimensional quantile prediction
Uncertainty calibration for probabilistic projection methods
Sampling hierarchies of discrete random structures
Functional variance estimation using penalized splines with principal component analysis
Multivariate locally stationary 2D wavelet processes with application to colour texture analysis
A general maximum likelihood analysis of overdispersion in generalized linear models
Bayesian numerical methods for nonlinear partial differential equations
Non-parametric maximum likelihood estimation of interval-censored failure time data subject to misclassification
A tutorial on support vector regression
Bayesian sequential analysis for multiple-arm clinical trials
Bayesian tests on components of the compound symmetry covariance matrix
Model-based clustering of multiple networks with a hierarchical algorithm
Optimal designs for nonlinear mixed-effects models using competitive swarm optimizer with mutated agents
A fast look-up method for Bayesian mean-parameterised Conway-Maxwell-Poisson regression models
Online robust estimation and bootstrap inference for function-on-scalar regression
Fast Bayesian inference in a class of sparse linear mixed effects models
Bayesian computation: a summary of the current state, and samples backwards and forwards
Between stability and higher-order asymptotics
Accelerating Metropolis-within-Gibbs sampler with localized computations of differential equations
A data-adaptive method for outlier detection from functional data
A mixture of experts regression model for functional response with functional covariates
Automatic Bayesian quantile regression curve fitting
A sign based loss approach to model selection in nonparametric regression
Computing location depth and regression depth in higher dimensions
The COR criterion for optimal subset selection in distributed estimation
On some consistent tests of mutual independence among several random vectors of arbitrary dimensions
Cauchy Markov random field priors for Bayesian inversion
Bayesian cross-validation by parallel Markov chain Monte Carlo
Fuzzy clustering algorithm for latent class model
A similarity-based Bayesian mixture-of-experts model
Evaluating Gaussian process metamodels and sequential designs for noisy level set estimation
Approximate Bayesian computation sequential Monte Carlo via random forests
A new p-value based multiple testing procedure for generalized linear models
Bayesian analysis of contingency tables: a simulation and graphics-based approach
A case study in non-centering for data augmentation: Stochastic epidemics
Subsampling sequential Monte Carlo for static Bayesian models
Automatic differentiation of Box-Cox transformations with application to random effects models for continuous non-normal response
Randomized algorithms of maximum likelihood estimation with spatial autoregressive models for large-scale networks
Distributed detection/localization of change-points in high-dimensional network traffic data
Distributed empirical likelihood inference with privacy guarantees
Efficient Bayesian estimation of the multivariate Double Chain Markov Model
RDELA - a Delaunay-triangulation-based, location and covariance estimator with high breakdown point
A Resampling Algorithm for Chaotic Time Series
Efficient modeling of quasi-periodic data with seasonal Gaussian process
Single-pass low-storage arbitrary quantile estimation for massive datasets
Two-dimensional generalisations of dynamic programming for image analysis
Gradient-free Gibbs sampler for shallow-wide Bayesian neural networks
Classifier-dependent feature selection via greedy methods
A Monte Carlo Markov chain algorithm for a class of mixture time series models
Randomized time Riemannian Manifold Hamiltonian Monte Carlo
Achieving limiting distributions for Markov chains using back buttons
Sampling from Dirichlet process mixture models with unknown concentration parameter: mixing issues in large data implementations
Conditional particle filters with diffuse initial distributions
Unlabelled landmark matching via Bayesian data selection, and application to cell matching across imaging modalities
Multiscale stick-breaking mixture models
Clustering longitudinal ordinal data via finite mixture of matrix-variate distributions
An online classification EM algorithm based on the mixture model
Fast generation of exchangeable sequences of clusters data
Bayesian variable selection for latent class analysis using a collapsed Gibbs sampler
Fast and robust estimators of variance components in the nested error model
Localizing the latent structure canonical uncertainty: entropy profiles for hidden Markov models
Computing least trimmed squares regression with the forward search
Nonparametric regression using linear combinations of basis functions
A generalized likelihood-based Bayesian approach for scalable joint regression and covariance selection in high dimensions
Adaptive ABC model choice and geometric summary statistics for hidden Gibbs random fields
Exact power computation for stratified dose-response studies
A permutation test for umbrella alternatives
Computer experiment designs for accurate prediction
Deletion diagnostics for marginal mean and correlation model parameters in estimating equations
Without-replacement sampling for particle methods on finite state spaces
Nonlinear mixed-effects scalar-on-function models and variable selection
Scale mixtures of multivariate centered skew-normal distributions
Sequential Sample Average Majorization-Minimization
Functional concurrent hidden Markov model
Calculating the normalising constant of the Bingham distribution on the sphere using the holonomic gradient method
A Hybrid Variational Bayesian Approach for Spatial Random Effects Structural Equation Modeling
Learning-based importance sampling via stochastic optimal control for stochastic reaction networks
Non-parametric smoothing of the location model in mixed variable discrimination
Bootstrap methods for stationary functional time series
Empirical likelihood inference for general transformation models with right censored data
Nonparametric multivariate density estimation using mixtures
Corrected p-values for tests based on estimated nuisance parameters
The ℓ 1 oblique procrustes problem
Robust rank screening for ultrahigh dimensional discriminant analysis
Control variates and importance sampling for efficient bootstrap simulations
Evaluations of FDR-controlling procedures in multiple hypothesis testing
Node deletion sequences in influence diagrams using genetic algorithms
Supervised learning via ensembles of diverse functional representations: the functional voting classifier
Correction: Unbiased and multilevel methods for a class of diffusions partially observed via marked point processes
Using conditional independence for parsimonious model-based Gaussian clustering
A hierarchical model for ordinal matrix factorization
A regularized bridge sampler for sparsely sampled diffusions
Gaussian Regularized Sliced Inverse Regression
On randomized sketching algorithms and the Tracy-Widom law
Accelerating Monte Carlo Markov chain convergence for cumulative-link generalized linear models
A Markov Chain Monte Carlo version of the genetic algorithm Differential Evolution: easy Bayesian computing for real parameter spaces
A finite mixture model for multivariate counts under endogenous selectivity
Asymptotic post-selection inference for regularized graphical models
Parallel and interacting stochastic approximation annealing algorithms for global optimisation
Approximate computations for binary Markov random fields and their use in Bayesian models
Introduction to "Quantitative bounds of convergence for geometrically ergodic Markov Chain in the Wasserstein distance with application to the Metropolis adjusted Langevin algorithm" by A. Durmus, É. Moulines
The direct use of likelihood for significance testing
Approximations for Gibbs Distribution Normalising Constants
Valid asymptotic inference after sufficient dimension reduction in a single-index framework
Confidence intervals and one-sample-based hypothesis testing for Cronbach's α coefficient for interval-valued data
Identifiability of discrete input-output hidden Markov models with external signals
Mixture reduction via predictive scores
A Conditional Autoregressive Gaussian Process for Irregularly Spaced Multivariate Data with Application to Modelling Large Sets of Binary Data
Variational Bayesian inference for models with nuisance parameters and an intractable likelihood
Moments and random number generation for the truncated elliptical family of distributions
Kernel discriminant analysis and clustering with parsimonious Gaussian process models
Fast post-process Bayesian inference with Variational Sparse Bayesian Quadrature
Kernel density classification and boosting: an L 2 analysis
Unbiased estimation of the gradient of the log-likelihood in inverse problems
Estimating the number of true null hypotheses in multiple hypothesis testing
Hyperparameter optimization for randomized algorithms: a case study on random features
Bayesian multiple comparison of models for binary data with inequality constraints
Hierarchical priors for Bayesian CART shrinkage
Heterogeneous Analysis of Longitudinal Profiles using Adaptive Banded Precision Matrices via Penalized Fusion
Information preserving statistical obfuscation
Correction to: Explainable generalized additive neural networks with independent neural network training
Bayesian inference via projections
Switched diffusion processes for non-convex optimization and saddle points search
Ensemble slice sampling
Parametric Bayesian inference for Y-linked two-sex branching models
Continuous monitoring for changepoints in data streams using adaptive estimation
Robust clustering tools based on optimal transportation
Dimension-independent spectral gap of polar slice sampling
MALA with annealed proposals: a generalization of locally and globally balanced proposal distributions
Semiparametric lack-of-fit tests in an additive hazard regression model
ML estimation for factor analysis: EM or non-EM?
Guest Editorial: Regularisation Methods in Regression and Classification
Changepoint detection in non-exchangeable data
Penalized robust estimating equation and variable selection in a partially linear single-index varying-coefficient model
Robust mixture modeling using the skew t distribution
A Metropolis-class sampler for targets with non-convex support
Adaptive evolutionary Monte Carlo algorithm for optimization with applications to sensor placement problems
Subgroup Analysis of Differential Networks with Latent Variables
Introduction to "Adaptive ABC model choice and geometric summary statistics for hidden Gibbs random fields" by J. Stoehr, P. Pudlo, L. Cucala
Bayesian Additive Regression Trees using Bayesian model averaging
Algebraic Methods for Polynomial Statistical Models
Penalized empirical likelihood inference for sparse additive hazards regression with a diverging number of covariates
Direct simulation for discrete mixture distributions
Langevin diffusions on the torus: estimation and applications
Stability of feature selection in classification issues for high-dimensional correlated data
Metropolis-Hastings algorithms with adaptive proposals
Goodness-of-fit tests in semi-linear models
Anytime parallel tempering
Markov chain Monte Carlo algorithms with sequential proposals
A branch-and-bound algorithm for the exact optimal experimental design problem
Efficient Bayesian analysis of multiple changepoint models with dependence across segments
Exact and computationally efficient Bayesian inference for generalized Markov modulated Poisson processes
Additive mixed models with approximate Dirichlet process mixtures: the EM approach
Bayesian quantile regression for partially linear additive models
Parallel ADMM Algorithm with Gaussian Back Substitution for High-Dimensional Quantile Regression and Classification
Variable selection for generalized linear mixed models by L 1-penalized estimation
Improving the EM algorithm for mixtures
Sufficient dimension reduction in regressions through cumulative Hessian directions
Bootstrapping and permuting paired t-test type statistics
Natural gradient hybrid variational inference with application to deep mixed models
Generalized additive models with flexible response functions
Constrained parsimonious model-based clustering
Quantile regression feature selection and estimation with grouped variables using Huber approximation
The effect of intrinsic dimension on the Bayes-error of projected quadratic discriminant classification
A mixed model approach to measurement error in semiparametric regression
Independence test via mutual information in the presence of measurement errors
On a differential equation approach to the weighted orthogonal Procrustes problem
Monte Carlo co-ordinate ascent variational inference
Cause-specific hazards model under covariate measurement error
Unbiased parameter estimation for bayesian inverse problems
A Bayesian nonparametric approach for clustering functional trajectories over time
Flexible parametric quantile regression model
Product-form estimators: exploiting independence to scale up Monte Carlo
An apparent paradox: a classifier based on a partially classified sample may have smaller expected error rate than that if the sample were completely classified
Adaptive thresholding of sequences with locally variable strength
Variational Bayesian analysis of survival data using a log-logistic accelerated failure time model
Phylourny: efficiently calculating elimination tournament win probabilities via phylogenetic methods
A SUR version of the Bichon criterion for excursion set estimation
Erratum to: Fast covariance estimation for sparse functional data
Improving flexibility and efficiency by adding parallelism to genetic algorithms
Automatically adapting the number of state particles in SMC 2
A parallel evolutionary multiple-try metropolis Markov chain Monte Carlo algorithm for sampling spatial partitions
Cases for the nugget in modeling computer experiments
Fast Gibbs sampling for the local-seasonal-global trend Bayesian exponential smoothing model
Variance reduction of estimators arising from Metropolis-Hastings algorithms
Coaching variables for regression and classification
Incomplete-data Fisher scoring method with steplength adjustment
Variable selection using axis-aligned random projections for partial least-squares regression
Random texture models for material structures
Model fitting and inference under latent equilibrium processes
Computing with Fisher geodesics and extended exponential families
Lazy ABC
Ideal bootstrap estimation of expected prediction error for k-nearest neighbor classifiers: Applications for classification and error assessment
Low-rank tensor reconstruction of concentrated densities with application to Bayesian inversion
A hybrid EM/Gauss-Newton algorithm for maximum likelihood in mixture distributions
Fisher Scoring for crossed factor linear mixed models
Comparing composite likelihood methods based on pairs for spatial Gaussian random fields
Dimension reduction for model-based clustering
Communication-efficient estimation for distributed subset selection
Bayesian analysis of some models that use the asymmetric exponential power distribution
Optimal linear projections for enhancing desired data statistics
Regression models for binary longitudinal responses
Computing highly accurate confidence limits from discrete data using importance sampling
Pointwise and functional approximations in Monte Carlo maximum likelihood estimation
Low-dimensional tracking of association structures in categorical data
Boosting with Bayesian stumps
Matching pursuit by undecimated discrete wavelet transform for non-stationary time series of arbitrary length
Restricted likelihood inference for generalized linear mixed models
Outlier detection in contingency tables based on minimal patterns
Rotation tests
Classification of multivariate functional data on different domains with Partial Least Squares approaches
Off-policy evaluation for tabular reinforcement learning with synthetic trajectories
Extended fiducial inference for individual treatment effects via deep neural networks
Dynamic model-based clustering for spatio-temporal data
Geometry-informed irreversible perturbations for accelerated convergence of Langevin dynamics
Large-scale kernel methods for independence testing
Implementation of saddlepoint approximations in resampling problems
Sequential sampling of junction trees for decomposable graphs
On the estimation of variance parameters in non-standard generalised linear mixed models: application to penalised smoothing
Regularized estimation for highly multivariate log Gaussian Cox processes
Bayesian modelling and computation utilising directed cycles in multiple network data
Tracking multiple moving objects in images using Markov Chain Monte Carlo
Nonparametric estimation of the link function including variable selection
Exact optimal experimental designs with constraints
Generating random numbers of prescribed distribution using physical sources
A hybrid Markov chain for the Bayesian analysis of the multinomial probit model
Fast matrix computations for functional additive models
Neural networks for scalar input and functional output
Optimal allocation of Monte Carlo simulations to multiple hypothesis tests
Metropolis-adjusted interacting particle sampling
On generalized degrees of freedom with application in linear mixed models selection
A communication-efficient, online changepoint detection method for monitoring distributed sensor networks
Randomized self-updating process for clustering large-scale data
Automating and evaluating reversible jump MCMC proposal distributions
Model uncertainty and variable selection in Bayesian lasso regression
Identifiable finite mixtures of location models for clustering mixed-mode data
Questioning normality: A study of wavelet leaders distribution
De-noising boosting methods for variable selection and estimation subject to error-prone variables
Sparse and geometry-aware generalisation of the mutual information for joint discriminative clustering and feature selection
On optimal multiple changepoint algorithms for large data
Random variate generation for the generalized inverse Gaussian distribution
Rate-optimal refinement strategies for local approximation MCMC
The conditional censored graphical lasso estimator
LARS-type algorithm for group lasso
COMBSS: best subset selection via continuous optimization
Variable selection and estimation for PSH regression models via generalized seamless-L 0 penalty
MCMC Sampler Convergence Rates for Hierarchical Normal Linear Models: A Simulation Approach
On Neyman's smooth tests for symmetry about an unknown center
Probabilistic linear solvers: a unifying view
On sequential Monte Carlo sampling methods for Bayesian filtering
Rank-based variable selection with censored data
Non parametric estimation of the structural expectation of a stochastic increasing function
Properties and Estimation of a Novel Skewed Generalized Normal Distribution
Importance sampling for partially observed temporal epidemic models
Bayesian quadrature with non-normal approximating functions
Random projections for Bayesian regression
Distributed subsampling for multiplicative regression
Approximate Bayesian computation methods
A mixture model for random graphs
Sequential Monte Carlo methods for mixtures with normalized random measures with independent increments priors
Sampling from the posterior distribution in generalized linear mixed models
Regularised PCA to denoise and visualise data
James E. Gentle: Computational statistics (Statistics and Computing Series) - Springer-Verlag, New York, April 2009, xxi+727 pages, ISBN 978-0-387-98143-7, DOI 10.1007/978-0-387-98144-4, $ 99.00
The birds and the bees: interactive graphics and problem solving in the teaching of statistics
Flexible spatio-temporal stationary variogram models
PCA-uCPD: an ensemble method for multiple change-point detection in moderately high-dimensional data
Statistical approaches in quantitative positron emission tomography
A Bayesian approach to modeling finite element discretization error
Optimal subsampling for generalized additive models on large-scale datasets
On Bayesian model and variable selection using MCMC
A non-stationary model for spatially dependent circular response data based on wrapped Gaussian processes
Mixtures of regressions with changepoints
Comprehensive study of variational Bayes classification for dense deep neural networks
Estimation of two-layer Gaussian mixture model for streaming longitudinal data in Bayesian framework
Testing common degree-correction parameters of multilayer networks
Convergence rate of multiple-try Metropolis independent sampler
Trajectory inference and parameter estimation in stochastic models with temporally aggregated data
Correction to: Finite mixtures of quantile and M-quantile regression models
On the optimality of the Oja's algorithm for online PCA
Retrospective Bayesian outlier detection in INGARCH series
A comparison of centring parameterisations of Gaussian process-based models for Bayesian computation using MCMC