但是如果卡不够,应用又没有时间限制,那么LIME是比gradient-based methods有优势的,因为不用反向传播,GPU只要走前向就可以了。 经过实验,LIME的采样点在1000个左右时在LLAMA-2的解释上效果很好,前提是sequence不能太长。当采样点足够时,LIME的效果比IG更好。注意,如果要把LIME用在language上,那么每个word的所有...
软件默认的是Least Squares Cell-Based方法,而且相信很多人在仿真时候,对于Gradient的离散方法都是采用默认的。 Gradients梯度需要离散的必要性不单单是为了在网格表面构建标量值,而且还是为了计算二次扩散项和速度导数的需要。 1. Green-Gauss Cell-Based Green-Gauss Cell-Based,顾名思义,基于网格中心(Cell-Based)计...
软件默认的是Least Squares Cell-Based方法,而且相信很多人在仿真时候,对于Gradient的离散方法都是采用默认的。 Gradients梯度需要离散的必要性不单单是为了在网格表面构建标量值,而且还是为了计算二次扩散项和速度导数的需要。 1. Green-Gauss Cell-Based Green-Gauss ...
Thresholding-based method classifies pixels into different regions by gray thresholding, thereby labeling different regions in an image. Thresholds can be obtained by a parametric or non-parametric method from the probability density function of gray histogram. The parametric methods have a large amount...
2. RADO methods 2.1. UQ methods The principles and implementations of SAGB are introduced in this section. UQ is the most time-consuming module in RADO, thus the sensitivity-based and model-based UQ methods are introduced briefly. Using the First-Order Sensitivities (FOS) and SOS, performance...
DeepExplain supports several methods. The main partition is betweengradient-based methodsandperturbation-based methods. The former are faster, given that they estimate attributions with a few forward and backward iterations through the network. The latter perturb the input and measure the change in out...
A new learning paradigm, called Graph Transformer Networks (GTN), allows such multi-module systems to be trained globally using Gradient-Based methods so as to minimize an overall performance measure. 现实生活中的文档识别系统是由多个模块组成的,包括字段提取、分割、识别和语言建模。一种新的学习范式...
即没有action value的估计值就无法进行action选择,也就没有Policy,这类方法被称为 value-based methods.其实我们可以直接产生不依赖于action value 的polcy ,这类直接生成action的方法就叫policy-based methods.他们关系如下: value-based方法,需要计算价值函数(value function),根据自己认为的高价值选择行(action)的...
2015). In contrast, gradient-based methods are generally more prone to explore the hypothesis space, before converging to a stationary point (assuming that the chosen step-size is not particularly small). 3.2 Methods based on (soft-) orthogonal relaxations Since the binary constraints in ...
As an alternative to these gradient-based methods, Powell's method is a gradient-free alternative for registration optimization. It uses iterative line search minimizations to find optimal values of individual variables i and determine the next step with a scalar variable αi. (24)xt+1=xt−∑...