Real-time detection of seizure activities in epileptic patients is crucial and can help improve
patients' quality of life. Accurate evaluation, pre-surgery assessments, seizure prevention …

Abstract Reproducing kernel Hilbert $ C^* $-module (RKHM) is a generalization of
reproducing kernel Hilbert space (RKHS) by means of $ C^* $-algebra, and the Perron …

This paper investigates a novel algorithmic approach to data representation based on kernel
methods. Assuming that the observations lie in a Hilbert space X, the introduced Kernel …

Machine learning has a long collaborative tradition with several fields of mathematics, such
as statistics, probability and linear algebra. We propose a new direction for machine …

Privacy-utility tradeoff remains as one of the fundamental issues of differentially private
machine learning. This paper introduces a geometrically inspired kernel-based approach to …

One percent of the world's population suffers from epilepsy, a chronic disorder characterized
by the occurrence of spontaneous seizures. About 30 percent of patients remain medically …

This paper develops a novel mathematical framework for collaborative learning by means of
geometrically inspired kernel machines which includes statements on the bounds of …

Hashing based approximate nearest neighbors (ANN) search has drawn considerable
attraction owing to its low-memory storage and hardware-level logical computing which is …

Machine learning has a long collaborative tradition with several fields of mathematics, such
as statistics, probability and linear algebra. We propose a new direction for machine …

Learning hash functions for high dimensional multi-modal data is of great interest for many
real-world retrieval applications in which data comes from diverse heterogeneous sources …