Personal Information
Entreprise/Lieu de travail
Lansing, Michigan Area United States
Profession
PHD Candidate
Secteur d’activité
Education
Site Web
http://www.msu.edu/
À propos
Passionate about data science, data mining, pattern recognition, and large scale data analysis
Solid understanding of statistical analysis methods, pattern recognition and machine learning
Proficient programming skills in R, python, MATLAB, C/C++, and developing robust numerical codes
Mots-clés
deep learning
clustering
wacv 2019
computer vision
wacv
soft biometrics
semi-adversarial networks
san
face recognition
artificial neural networks
pattern recognition
algorithms
big data
truetime
vector clock
google
logical time
disk-based
k-means
databases
Tout plus
Présentations
(5)J’aime
(3)Optimal interval clustering: Application to Bregman clustering and statistical mixture learning
Frank Nielsen
•
il y a 9 ans
Chap8 basic cluster_analysis
guru_prasadg
•
il y a 12 ans
MusicMood - Machine Learning in Automatic Music Mood Prediction Based on Song Lyrics
Sebastian Raschka
•
il y a 9 ans
Personal Information
Entreprise/Lieu de travail
Lansing, Michigan Area United States
Profession
PHD Candidate
Secteur d’activité
Education
Site Web
http://www.msu.edu/
À propos
Passionate about data science, data mining, pattern recognition, and large scale data analysis
Solid understanding of statistical analysis methods, pattern recognition and machine learning
Proficient programming skills in R, python, MATLAB, C/C++, and developing robust numerical codes
Mots-clés
deep learning
clustering
wacv 2019
computer vision
wacv
soft biometrics
semi-adversarial networks
san
face recognition
artificial neural networks
pattern recognition
algorithms
big data
truetime
vector clock
google
logical time
disk-based
k-means
databases
Tout plus