About Lama Burhan Niyazi Lama Burhan Niyazi Ph.D. (former), Electrical and Computer Engineering Random Matrix Theory machine learning Ph.D. degree in the Communication Theory Lab (CTL) under the joint supervision of Professor Mohamed-Slim Alouini and Professor Tareq Al-Naffouri , King Abdullah University of Science and Technology (KAUST) Events Presented Events Nov 26 - Dec 2, 2023 Analysis and Design of Linear Classifiers for High-Dimensional, Small Sample Size Data Using Asymptotic Random Matrix Theory Lama Burhan Niyazi, Ph.D. (former), Electrical and Computer Engineering Nov 26, 11:30 - 13:30 B1 L3 R3119 Due to a variety of potential barriers to sample acquisition, many of the datasets encountered in important classification applications, ranging from tumor identification to facial recognition, are characterized by small samples of high-dimensional data. In such situations, linear classifiers are popular as they have less risk of overfitting while being faster and more interpretable than non-linear classifiers. They are also easier to understand and implement for the inexperienced practitioner.
Analysis and Design of Linear Classifiers for High-Dimensional, Small Sample Size Data Using Asymptotic Random Matrix Theory Lama Burhan Niyazi, Ph.D. (former), Electrical and Computer Engineering Nov 26, 11:30 - 13:30 B1 L3 R3119 Due to a variety of potential barriers to sample acquisition, many of the datasets encountered in important classification applications, ranging from tumor identification to facial recognition, are characterized by small samples of high-dimensional data. In such situations, linear classifiers are popular as they have less risk of overfitting while being faster and more interpretable than non-linear classifiers. They are also easier to understand and implement for the inexperienced practitioner.
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