TY  - GEN
N2  - We evaluate the performance of both of the proposed methods on several density estimation tasks from the UCI Repository as well as our corpus of Monkey vocalizations, recorded at the Oregon National Primate Research Center. We find that our methods represent the data consistently better than Gaussian mixture models with equivalent number of parameters. We also evaluate our proposed methods for building generative classifiers for a number of classification tasks from the UCI Repository. We find that these generative models perform as well or better than discriminative classifiers such as a Support Vector Machine (SVM).
AB  - We evaluate the performance of both of the proposed methods on several density estimation tasks from the UCI Repository as well as our corpus of Monkey vocalizations, recorded at the Oregon National Primate Research Center. We find that our methods represent the data consistently better than Gaussian mixture models with equivalent number of parameters. We also evaluate our proposed methods for building generative classifiers for a number of classification tasks from the UCI Repository. We find that these generative models perform as well or better than discriminative classifiers such as a Support Vector Machine (SVM).
AD  - Oregon Health and Science University
T1  - Copula models for multivariate density estimation, classification and robust speech recognition
DA  - 2018-12-13
AU  - Bayestehtashk, Alireza
L1  - https://digitalcollections.ohsu.edu/record/41281/files/Bayestehtashk.Alriza.2018.pdf
PB  - Oregon Health and Science University
LA  - eng
PY  - 2018-12-13
ID  - 41281
L4  - https://digitalcollections.ohsu.edu/record/41281/files/Bayestehtashk.Alriza.2018.pdf
KW  - Probability Theory
KW  - Models, Statistical
KW  - Speech Recognition Software
KW  - Vocalization, Animal
KW  - copula models
TI  - Copula models for multivariate density estimation, classification and robust speech recognition
Y1  - 2018-12-13
L2  - https://digitalcollections.ohsu.edu/record/41281/files/Bayestehtashk.Alriza.2018.pdf
LK  - https://digitalcollections.ohsu.edu/record/41281/files/Bayestehtashk.Alriza.2018.pdf
UR  - https://digitalcollections.ohsu.edu/record/41281/files/Bayestehtashk.Alriza.2018.pdf
ER  -