204 citations · 228 across the 10 of their papers we have counts for
4 papers · 1 filter
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…
Relative intrinsic dimensionality is intrinsic to learning
Oliver J. Sutton, Qinghua Zhou, Alexander N. Gorban +1
High dimensional data can have a surprising property: pairs of data points may be easily separated from each other, or even from arbitrary subsets, with high probability using just…
Towards a mathematical understanding of learning from few examples with nonlinear feature maps
Oliver J. Sutton, Alexander N. Gorban, Ivan Y. Tyukin
We consider the problem of data classification where the training set consists of just a few data points. We explore this phenomenon mathematically and reveal key relationships bet…
Principal Graphs and Manifolds
A. N. Gorban, A. Y. Zinovyev
In many physical, statistical, biological and other investigations it is desirable to approximate a system of points by objects of lower dimension and/or complexity. For this purpo…