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- reordering of the Schur factorizations and estimating condition numbers. Dense and banded matrices are handled...
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- authors concentrate on the simplest nonparametric curve estimation setting, namely density and regression estimation. Special...
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- optimization problems theoretical convergence multiclass classification probability estimates and parameter selection are discussed in detail...
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- stochastic objective functions, based on adaptive estimates of lower-order moments. The method is straightforward...
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- restores the missing Rarefaction wave by some estimates, like linearisations, these can be simple...
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- might not be the inverse of the estimated covariance, and occasionally it fails to converge ... this dual, the target of estimation is Σ, the covariance matrix, rather than the precision...
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- fine-grained fitness assignment strategy, a density estimation technique, and an enhanced archive truncation method...
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- Smoothing spline ANOVA models Nonparametric function estimation with stochastic data, otherwise known as smoothing ... time data; (ii) density and conditional density estimation under a variety of sampling schemes ... hazard rate estimation with censored life time data and covariates. The unifying themes...
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- automatic scaling of linear contraints, and automatic estimation of some or all gradients. Upper...
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- program which creates, simulates data from, estimates, tests, predicts with, and searches for causal...
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- Model-Based Clustering, Classification, and Density Estimation , Normal Mixture Modeling fitted via EM algorithm ... Model-Based Clustering, Classification, and Density Estimation, including Bayesian regularization...
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- generalization performance efficiently. It includes two efficient estimation methods for both error rate and precision/recall ... XiAlpha-estimates [Joachims, 2002a, Joachims, 2000b] can be computed at essentially no computational expense ... they are conservatively biased. Almost unbiased estimates provides leave-one-out testing. SVMlight exploits that...
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- tridiagonal linear systems of equations, condition estimation and iterative refinement, for LU and Cholesky factorization...
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- represent the error statistics of the model estimate, it applies ensemble integrations to predict...
- Referenced in 394 articles
- Reliable stopping criteria are derived, along with estimates of standard errors...
- Referenced in 384 articles
- simplification, subdivision and parameterization, as well as estimation of local differential properties, and approximation...
- Referenced in 346 articles
- offers researchers a wide choice of models, estimators, and algorithms in a program that...
- Referenced in 286 articles
- sampling (NUTS, HMC) and penalized maximum likelihood estimation with Optimization (BFGS). Stan is coded...
System Identification Toolbox
- Referenced in 178 articles
- under either GNU Octave or MATLAB, for estimation of dynamic systems. A wide range ... standard estimation approaches are supported. These include the use of non-parametric, subspace-based ... investigated by the authors. These include the estimation of non-linear models...
- Referenced in 193 articles
- also provided to equilibrate the system, estimate the condition number, calculate the relative backward error ... estimate error bounds for the refined solutions...