Classical data mining algorithms implicitly assume complete access to all data, either in centralized or federated form. However, privacy and security concerns often prevent sharin...
Support vector machines are trained by solving constrained quadratic optimization problems. This is usually done with an iterative decomposition algorithm operating on a small wor...
There are many applications related to singly linearly constrained quadratic programs subjected to upper and lower bounds. In this paper, a new algorithm based on secant approximat...
A maximum-entropy approach to generative similarity-based classifiers model is proposed. First, a descriptive set of similarity statistics is assumed to be sufficient for classifi...
We develop a new multiclass classification method that reduces the multiclass problem to a single binary classifier (SBC). Our method constructs the binary problem by embedding sm...