90 citations · 294 across the 20 of their papers we have counts for
20 papers
When fractional quasi p-norms concentrate
Ivan Y. Tyukin, Bogdan Grechuk, Evgeny M. Mirkes +1
Concentration of distances in high dimension is an important factor for the development and design of stable and reliable data analysis algorithms. In this paper, we address the fu…
Weakly Supervised Learners for Correction of AI Errors with Provable Performance Guarantees
Ivan Y. Tyukin, Tatiana Tyukina, Daniel van Helden +6
We present a new methodology for handling AI errors by introducing weakly supervised AI error correctors with a priori performance guarantees. These AI correctors are auxiliary map…
What is Hiding in Medicine's Dark Matter? Learning with Missing Data in Medical Practices
Neslihan Suzen, Evgeny M. Mirkes, Damian Roland +3
Electronic patient records (EPRs) produce a wealth of data but contain significant missing information. Understanding and handling this missing data is an important part of clinica…
Agile gesture recognition for capacitive sensing devices: adapting on-the-job
Ying Liu, Liucheng Guo, Valeri A. Makarov +4
Automated hand gesture recognition has been a focus of the AI community for decades. Traditionally, work in this domain revolved largely around scenarios assuming the availability…
Domain Adaptation Principal Component Analysis: base linear method for learning with out-of-distribution data
Evgeny M Mirkes, Jonathan Bac, Aziz Fouché +3
Domain adaptation is a popular paradigm in modern machine learning which aims at tackling the problem of divergence (or shift) between the labeled training and validation datasets…
An Informational Space Based Semantic Analysis for Scientific Texts
Neslihan Suzen, Alexander N. Gorban, Jeremy Levesley +1
One major problem in Natural Language Processing is the automatic analysis and representation of human language. Human language is ambiguous and deeper understanding of semantics a…