Demographic bias gaps are closing in face recognition, but how training images are sourced is becoming the field’s biggest privacy fight.

A deep-learning analysis of three-dimensional optical coherence tomography scans shows promising accuracy in distinguishing ...

Overview Understanding key machine learning algorithms is crucial for solving real-world data problems effectively.Data scientists should master both supervised ...

Many of the classification algorithms developed in the machine learning literature, including the support vector machine and boosting, can be viewed as minimum contrast methods that minimize a convex ...

For the uninitiated, the K-nearest neighbors or kNN Algorithm is a very simple classification algorithm that uses similarities between given sets of data and a data point being examined to predict ...

Another aspect of our analysis is to demonstrate the consistency of certain classification methods using convex risk minimization. This study sheds light on the good performance of some recently ...

DTSA 5510 Unsupervised Algorithms in Machine Learning Same as CSCA 5632 Specialization: Machine Learning Instructor: Geena Kim, Assistant Teaching Professor Prior knowledge needed: Calculus, Linear ...