π‘ƒπ‘œπ‘ π‘–π‘‘π‘–π‘£π‘’π‘‘π‘’π‘“π‘–π‘›π‘–π‘‘π‘’π‘“π‘’π‘›π‘π‘‘π‘–π‘œπ‘›π‘  and kernel analysis

2018 β—½  
pp. 175-217
Keyword(s):  
Kernel Analysis

scholarly journals Benefits of Jointly Training Autoencoders: An Improved Neural Tangent Kernel Analysis

2021 β—½  
pp. 1-1
Author(s):  
Thanh V. Nguyen β—½  
Raymond K. W. Wong β—½  
Chinmay Hegde
Keyword(s):  
Kernel Analysis

Asynchronous kernel analysis for binary mixture solutions of ethanol and carboxylic acids

2008 β—½  
Vol 883-884 β—½  
pp. 27-30 β—½  
Author(s):  
Hideyuki Shinzawa β—½  
Makio Iwahashi β—½  
Isao Noda β—½  
Yukihiro Ozaki
Keyword(s):  
Binary Mixture β—½  
Carboxylic Acids β—½  
Kernel Analysis

Wiener kernel analysis of responses from anteroventral cochlear nucleus neurons

Hearing Research β—½  
1984 β—½  
Vol 14 (2) β—½  
pp. 155-174 β—½  
Author(s):  
Robert E. Wickesberg β—½  
John W. Dickson β—½  
Mary Morton Gibson β—½  
C. Daniel Geisler
Keyword(s):  
Cochlear Nucleus β—½  
Kernel Analysis β—½  
Wiener Kernel β—½  
Anteroventral Cochlear Nucleus

scholarly journals Kernel Analysis Based on Dirichlet Processes Mixture Models

Entropy β—½  
10.3390/e21090857 β—½  
2019 β—½  
Vol 21 (9) β—½  
pp. 857
Author(s):  
Jinkai Tian β—½  
Peifeng Yan β—½  
Da Huang
Keyword(s):  
Mixture Models β—½  
Crucial Role β—½  
Gaussian Mixture Models β—½  
Gaussian Process Regression β—½  
Gaussian Mixture β—½  
Spectral Domain β—½  
Dirichlet Processes β—½  
Number Of Components β—½  
Kernel Analysis β—½  
Nonparametric Bayesian Models

Kernels play a crucial role in Gaussian process regression. Analyzing kernels from their spectral domain has attracted extensive attention in recent years. Gaussian mixture models (GMM) are used to model the spectrum of kernels. However, the number of components in a GMM is fixed. Thus, this model suffers from overfitting or underfitting. In this paper, we try to combine the spectral domain of kernels with nonparametric Bayesian models. Dirichlet processes mixture models are used to resolve this problem by changing the number of components according to the data size. Multiple experiments have been conducted on this model and it shows competitive performance.

scholarly journals Heat kernel analysis on semi-infinite Lie groups

2009 β—½  
Vol 257 (11) β—½  
pp. 3552-3592 β—½  
Author(s):  
Tai Melcher
Keyword(s):  
Heat Kernel β—½  
Lie Groups β—½  
Kernel Analysis β—½  
Heat Kernel Analysis

Data‐Variant Kernel Analysis

2015 β—½  
Author(s):  
Yuichi Motai, Ph.D.
Keyword(s):  
Kernel Analysis

scholarly journals Heterogeneous Distance Learning Based on Kernel Analysis-Synthesis Dictionary for Semi-Supervised Image to Video Person Re-Identification

IEEE Access β—½  
2020 β—½  
Vol 8 β—½  
pp. 169663-169675
Author(s):  
Xiaoke Zhu β—½  
Pengfei Ye β—½  
Xiao-Yuan Jing β—½  
Xinyu Zhang β—½  
Xiang Cui β—½  
...  
Keyword(s):  
Distance Learning β—½  
Kernel Analysis
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