setting the weight of each iteration value according to a weight resetting formula to get a weighted convex optimization problem model, wherein the weight resetting formula is a formula for calculating the corresponding weight according to each iteration value, a core parameter Beta and a preset par...
The focus of the study is to analyze stability results and to establish optimal error estimates, up to a logarithmic factor, for both the solution and the flux in L2-norm when the initial data u0∈H01(Ω)∩H2(Ω). Additionally, an error estimate in L∞-norm is derived for 2D problems...
2.2. L1-norm F-transform For some fuzzy r-partition (P,A,r) of [a,b] and a function f:[a,b]⟶R, we have seen that the direct F-transform of f, as in the paper [32], is such that each Fk minimizes the function Φk(y)=∫ab|f(x)−y|2Ak(x)dx with y∈R; Φk(...
Identification of DNA-binding proteins by Kernel Sparse Representation via [formula omitted]-matrix norm One advantage of KSRC is that it can efficiently learn high-dimensional features of protein sequences without being affected by dimensional. In addition, K... Y Ming,H Liu,Y Cui,... - 《...
摘要: Stability and convergence of the L1 formula on non 关键词: fractional subdiffusion equations nonuniform L1 formula discrete fractional Gronwall inequality global consistency analysis sharp error estimate DOI: 10.1137/17M1131829 年份: 2018
This article proposes the fast L1 alternating direction implicit (ADI) finite difference and compact difference schemes to solve the fractional telegraph equation in three-dimensional space. The fully-discrete fast L1 ADI finite difference scheme can be established via the fast L1 formula for the appr...
Note that 2n is exactly the volume of the unit sphere on the ℓ1 norm. It is worth pointing out that the proof of this discrete inequality is similar on spirit of our proof on the continuous setting and is based on the entropy inequalities. It is possible that the equivalences obtained...
L1-norm-based 2DPCA In this paper, we first present a simple but effective L1-norm-based two-dimensional principal component analysis (2DPCA). Traditional L2-norm-based least ... X Li,Y Pang,Y Yuan 被引量: 121发表: 2010年 A pure [formula omitted]-norm principal component analysis The ...
consider penalized SVM problems involving the minimization of a hinge-loss function with a convex sparsity-inducing regularizer such as: the L1-norm on the coefficients, its grouped generalization and the sorted L1-penalty (aka Slope). ... A Dedieu,R Mazumder,H Wang - 《Journal of Machine Lea...
Corrected label smoothing formula for cross entropy loss 900bd17 awni requested changes Dec 15, 2023 View reviewed changes Member awni left a comment Awesome! This is great! I left a few comments. Also I noticed you changed the reductions from 'none' to `mean'. What was the motivation...