Online learning with kernel regularized least mean square algorithms. Knowledge-Based Systems, 2014,59(2):21-32. [doi: 10.1016/j.knosys.2014.02.005]H. Fan, Q. Song, and S. B. Shrestha, "Online learning with kernel regularized least mean square algorithms," Knowledge-Based Systems, vol. ...
Apart from 2 or 3 exceptions, all of the gene sets identified under the various algorithms with a nominal unadjusted p-value of 0.05, including the 10 gene sets determined by GSEA-limma, are a subset of the 50 gene sets located with RCMAT. These results also largely encompass the results...
Besides the above prediction algorithms, some novel algorithms based on maximum-likelihood7,9,10 have been proposed. For the hierarchical structure of networks, Clauset et al. 9 proposed a model to infer hierarchical structure from network and applied it to solve the link prediction problem. ...
Traction Force Microscopy (TFM) is a widespread technique to estimate the tractions that cells exert on the surrounding substrate. To recover the tractions, it is necessary to solve an inverse problem, which is ill-posed and needs regularization to make the solution stable. The typical regulariza...
9 / 86 Background Today, we introduce two Stata packages: LASSOPACK (including lasso2, cvlasso & rlasso) implements penalized regression methods: LASSO, elastic net, ridge, square-root LASSO, adaptive LASSO. uses fast path-wise coordinate descent algorithms (Friedman et al., 2007). three ...
Our implementation of the SIMPLER algorithm was validated with the bidimensional lid-driven cavity flow problem, known in the literature as a benchmark for testing CFD algorithms [46–48]. All algorithms were implemented in Matlab (The MathWorks, Inc., Natick, MA, USA). Linear systems were sol...
Luo, Y., Huang, W., Li, X., Zhang, A.R.: Recursive importance sketching for rank constrained least squares: algorithms and high-order convergence. arXiv preprintarXiv:2011.08360(2020) Maronna, R.A., Martin, R.D., Yohai, V.J., Salibián-Barrera, M.: Robust Statistics: Theory and...
Kriegel, H.P., Kröger, P., Schubert, E., Zimek, A.: A general framework for increasing the robustness of PCA-based correlation clustering algorithms. In: Scientific and Statistical Database Management. Lecture Notes in Computer Science, vol. 5069, pp. 418–435 (2008) Kwak, N.: Princip...
We present 1 norm and approximate 0 norm regularized RTLS algorithms, and we elaborate on the selection of algorithm parameters. Simulation results show that the presented algorithms outperform the existing RLS and RTLS algorithms significantly in terms of mean square deviation (MSD). Furthermore, we...
The Wilcoxon signed-rank test is further used to verify that the prediction performance of the IPSO-RELM model is significantly different from the other developed algorithms. Because this study considers multiple historical environmental factors that affect greenhouse temperature, it is applicable to ...