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...
For enhancing the spectral resolution, the merging of Pure-Shift methods recognized for line narrowing with solvent elimination schemes was implemented in the context of mixtures containing protonated solvents. One more step was achieved to further enhance the resolution power on compact systems, thanks...
In the first talk, we provide a tutorial overview of most of the main approaches currently used for carrying out simulation optimization, which includes stochastic approximation, response surface methodology, and sample average approximation, as well as some random search methods. Simple examples will ...
and the final result tends to be affected by initial conditions. In the non-parameterization methods, thresholds is determined by solving an optimization problem with objective functions such as between-class variance (Otsu, 1979), one-dimensional entropy (Kapur et al., 1985, Pun, 1980), two-...
The performance parameters were fast calculated by a one-dimensional analysis program, thus the UQ and optimization methods have little impact on the optimization efficiency. Kamenik et al.11, Gao et al.12 introduced a RADO method for the design optimization of turbomachinery blades considering ...
M. (2012). Gradient-based stochastic optimization methods in Bayesian experimental design. Technical Report Massachusetts Institute of Technology, Cambridge.Huan X, Marzouk YM. 2012. Gradient-based stochastic optimization methods in Bayesian experimental design . ( http://arxiv.org/abs/1212.2228 )...
Theoretical or Mathematical/ autoregressive moving average processes convergence gradient methods identification nonlinear systems recursive estimation search problems stochastic processes/ iterative gradient-based identification algorithm recursive stochastic gradient-based identification algorithm Hammerstein nonlinear ARMA...
Methods marked with (*) are implemented as modified chain-rule, as better explained inTowards better understanding of gradient-based attribution methods for Deep Neural Networks, Anconaet al, ICLR 2018. As such, the result might be slightly different from the original implementation. ...
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...
The problem of explaining complex machine learning models, including Deep Neural Networks, has gained increasing attention over the last few years. While several methods have been proposed to explain network predictions, the definition itself of explanat