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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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Computational Optimizations for Machine Learning
| Computational Optimizations for Machine Learning |
| Autore | Gabbay Freddy |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 online resource (276 p.) |
| Soggetto topico |
Mathematics & science
Research & information: general |
| Soggetto non controllato |
ARIMA model
artificial intelligence autoencoders bed roughness bio-inspired algorithms CNN architecture computational intelligence convolutional neural network deep compression deep learning deep neural networks DNN energy dissipation evolution of weights evolutionary algorithms evolutionary computation feature selection floating-point numbers FLOW-3D generalization error genetic algorithms hardware acceleration Heating, Ventilation and Air Conditioning (HVAC) hydraulic jumps low power machine learning meta-heuristic optimization metaheuristics search model predictive control multi-objective optimization nature inspired algorithms neural networks nonlinear systems online model selection online optimization precipitation nowcasting quantization radar data recurrent neural networks ReLU sensitivity analysis smart building soft computing swarm intelligence time series analysis training |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557610303321 |
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Gabbay Freddy
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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