Convergence analysis of an adaptive pseudolinear-regression notch filtering algorithm," Circuits Syst. Signal Process., vol. 10, no. 2, pp. 245-259, 1991.P. Stoica and A. Nehorai, \Convergence analysis of an ad
Combining this alternative regression model with a default prior on the unknown parameters results in a highly intractable posterior density. Fortunately, there is a simple dataaugmentation (DA) algorithm that can be used to explore this posterior. This paper provides conditions (on $h$) for ...
In addition, it supports linear equality and inequality constraints on the parameter vector. The optimization algorithm has a provable linear convergence rate. The per-iteration computational complexity is linear in the sample size. Additional information can be located on the homepage of Rehline (htt...
it is determined by whether the operator’s calculation is prone to overflow or underflow; that is, it is determined by numerical safety. For example, forLinear, it is included in the autocast-to-FP16 list of PyTorch, which means
In addition, we provide an effective way of setting suitable smoothing parameters in the training process to bridge the gap between the convergence analysis based on the two different cost functions. 3) The weak and strong convergence of the proposed algorithm with smoothing approximation have been ...
SpikeProp algorithm is based on gradient descent method for SNNs. But it is difficult for normal SNNs to prove the convergence. In this paper, a smoothing L1∕2 regularization term is introduced into the error function as a penalty for the SpikeProp algorithm. The approach tries to constrain so...
Conclusions: Automatically tunable burn-in multiple-chain MCMC provides an accurate and cost-effective tool for high-performance computing of Bayesian genomic prediction models, and this algorithm is generally applicable to high-performance computing of any complex Bayesian statistical model. Keywords: ...
Results Among the principal causes is a failure of the fitting algorithm to converge despite the log-likelihood function having a single finite maximum. Despite these limitations, log-binomial models are a viable option for epidemiologists wishing to describe the relationship between a set of ...
edges in the communication network affects the convergence rate, so that faster convergence can be engineered by acting on the underlying network rather than on the averaging algorithm. Several studies deployed this approach on consensus algorithms, where more performing graphs were obtained by ...
Sequences were aligned using the Muscle algorithm in Geneious Prime v2020.1.2 (Biomatters Ltd.). The final alignment file is available in fasta format and archived in https://doi.org/10.5281/zenodo.6946172. Genbank accession numbers of gene sequences used are ...