Results 61 to 70 of about 172,692 (312)
A Survey of Tuning Parameter Selection for High-Dimensional Regression [PDF]
, 2020 Penalized (or regularized) regression, as represented by lasso and its variants, has become a standard technique for analyzing high-dimensional data when the number of variables substantially exceeds the sample size.
Wang, Lan, Wu, Yunan
core +1 more source
FEBS Open Bio, EarlyView.The dFoCC pipeline starts with observed DED and resting‐state coordinates, which are then used to generate a library of triggered states. Correlation analysis of the calculated DED features of each candidate vs observed DED permits quantitative evaluation of candidate structural quality.
Meng Iao Fong +3 more
wiley +1 more source
Explore the Principles of Prompt Tuning and the Progress of Research [PDF]
ITM Web of ConferencesPrompt Tuning is a lightweight fine-tuning method that demonstrates efficient task adaptation and parameter efficiency for pre-trained language models (PLMs). Prompt Tuning highlights an important contribution to the advancement of NLP technology.
Zheng Tongxin
doaj +1 more source
Bioinspired parameter tuning of classifiers [PDF]
, 2009 Aprendizado de máquina é uma área de pesquisa na qual se investiga como desenvolver sistemas capazes de aprender com a experiência. Muitos algoritmos de aprendizado possuem parâmetros cujos valores devem ser especificados pelo usuário.
André Luis Debiaso Rossi +1 more
core +1 more source
EDGETUNE: Inference-Aware Multi-Parameter Tuning [PDF]
, 2022 Deep Neural Networks (DNNs) have demonstrated impressive performance on many machine-learning tasks such as image recognition and language modeling, and are becoming prevalent even on mobile platforms.
Schiavoni, Valerio (author) +3 more
core +1 more source
Directed evolution of enzymes at the crossroads of tradition and innovation
FEBS Open Bio, EarlyView.An iterative cycle of data‐driven enzyme optimization comprising four stages: genetic diversification of a template enzyme, expression of protein variants, high‐throughput evaluation, and machine‐learning‐guided redesign of the next variant library.
Maria Tomkova +2 more
wiley +1 more source
Shrinkage Tuning Parameter Selection with a Diverging number of Parameters
Journal of the Royal Statistical Society Series B: Statistical Methodology, 2008 SummaryContemporary statistical research frequently deals with problems involving a diverging number of parameters. For those problems, various shrinkage methods (e.g. the lasso and smoothly clipped absolute deviation) are found to be particularly useful for variable selection. Nevertheless, the desirable performances of those shrinkage methods heavily
Wang, H., Li, B., Leng, C.
openaire +1 more source
Novel fuzzy logic controllers with self-tuning capability [PDF]
, 2008 Two controllers which extend the PD+I fuzzy logic controller to deal with the plant having time varying nonlinear dynamics are proposed. The adaptation ability of the first self tuning PD+I fuzzy logic controller (STPD+I_31) is achieved by adjusting the ...
Lotfi, A, Teng, FC, Tsoi, AC
core
Tuning Parameter Tolerance Design: Foundations, Methods, and Measures [PDF]
, 2000 In this paper, a novel technique is presented to solve tolerance design problems. To achieve the desired performance tolerance, the technique uses a subtle, but significant, change in the design: the addition of a tuning parameter in place of an increase
McAdams, Daniel A., Wood, Kristin L.
core +2 more sources
MagmaFlow: A desktop platform for artificial intelligence‐driven expression analysis
FEBS Open Bio, EarlyView.MagmaFlow is a free, no‐code platform for gene expression analysis. It generates interactive volcano plots, links genes to literature, pathways, and diseases, prioritizes candidates using millions of publications, identifies affected biological processes, builds network diagrams, and exports publication‐ready figures and reports for macOS and Windows ...
Carlos E. Buss +7 more
wiley +1 more source