Robust generalized canonical correlation analysis
Generalized canonical correlation analysis (GCCA) has been widely used for classification
and regression problems. The key idea of GCCA is to map the data from different views into …
and regression problems. The key idea of GCCA is to map the data from different views into …
Tensor canonical correlation analysis with convergence and statistical guarantees
YL Chen, M Kolar, RS Tsay - Journal of Computational and …, 2021 - Taylor & Francis
In many applications, such as classification of images or videos, it is of interest to develop a
framework for tensor data instead of an ad-hoc way of transforming data to vectors due to the …
framework for tensor data instead of an ad-hoc way of transforming data to vectors due to the …
Existing approaches in Ear biometrics
G Kaur, HK Verma - 2022 IEEE 4th International Conference on …, 2022 - ieeexplore.ieee.org
Biometric authentication is a self-sufficient technique to prove one's identity that could be
used in various security authentication platforms such as airport immigration control …
used in various security authentication platforms such as airport immigration control …
Stochastic and Online Learning with Applications to Machine Learning and Statistics
YL Chen - 2021 - search.proquest.com
This dissertation develops rigorous analyses of stochastic and online learning with
applications to modern machine learning models and statistical methodologies. There is no …
applications to modern machine learning models and statistical methodologies. There is no …
A latent variable model for two-dimensional canonical correlation analysis and the variational inference
The probabilistic dimension reduction has been and is a major concern. Probabilistic
models provide a better interpretability of the dimension reduction methods and present a …
models provide a better interpretability of the dimension reduction methods and present a …