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Approximate Bayesian Inference
| Approximate Bayesian Inference |
| Autore | Alquier Pierre |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 online resource (508 p.) |
| Soggetto topico |
Mathematics and Science
Research and information: general |
| Soggetto non controllato |
approximate Bayesian computation
Approximate Bayesian Computation approximate Bayesian computation (ABC) Bayesian inference Bayesian sampling Bayesian statistics Bethe free energy bifurcation complex systems control variates data imputation data streams deep learning differential evolution differential privacy (DP) discrete state space dynamical systems Edward-Sokal coupling entropy ergodicity expectation-propagation factor graphs fixed-form variational Bayes Gaussian generalisation bounds Gibbs posterior gradient descent greedy algorithm Hamilton Monte Carlo hyperparameters integrated nested laplace approximation Kullback-Leibler divergence Langevin dynamics Langevin Monte Carlo Laplace approximations machine learning Markov chain Markov chain Monte Carlo Markov Chain Monte Carlo Markov kernels MCMC MCMC-SAEM mean-field message passing meta-learning Monte Carlo integration network modeling network variability neural networks no free lunch theorems non-reversible dynamics online learning online optimization PAC-Bayes PAC-Bayes theory particle flow principal curves priors probably approximately correct regret bounds Riemann Manifold Hamiltonian Monte Carlo robustness sequential learning sequential Monte Carlo Sequential Monte Carlo sleeping experts sparse vector technique (SVT) statistical learning theory statistical mechanics Stiefel manifold stochastic gradients stochastic volatility thinning variable flow variational approximations variational Bayes variational free energy variational inference variational message passing |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910576874903321 |
Alquier Pierre
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Nonparametric Statistical Inference with an Emphasis on Information-Theoretic Methods
| Nonparametric Statistical Inference with an Emphasis on Information-Theoretic Methods |
| Autore | Mielniczuk Jan |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 online resource (226 p.) |
| Soggetto topico |
History of engineering and technology
Mechanical engineering and materials Technology: general issues |
| Soggetto non controllato |
adaptive splines
archimedean copula B-splines change points CIFE CMI conditional infomax feature extraction conditional mutual information consistency consistent selection entropy estimation extreme-value copula gaussian mixture generalized information criterion generative tree model high-dimensional regression high-dimensional time series influence functions information measures information theory JMI joint mutual information criterion kernel estimation learning systems loss function Markov blanket maximum likelihood estimation minimum distance estimation misclassification risk misspecification model misspecification multivariate analysis n/a network estimation nonparametric variable selection criteria nonstationarity parameter estimation penalized estimation prediction methods privacy random predictors right-censored data robustness semiparametric regression statistical learning theory subgaussianity supervised classification synthetic data transformation tail dependency time series variable selection consistency |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910576873203321 |
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Mielniczuk Jan
|
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| MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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