Blessing of dimensionality: mathematical foundations of the statistical physics of data

Stochastic separation theorems

(2017) A.N. Gorban et al.   NEURAL NETWORKS

Probabilistic lower bounds for approximation by shallow perceptron networks

(2017) Věra Kůrková et al.   NEURAL NETWORKS

Randomness in neural networks: an overview

(2017) Simone Scardapane et al.   Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery

Stochastic Configuration Networks: Fundamentals and Algorithms

(2017) Dianhui Wang et al.   IEEE Transactions on Cybernetics

Approximation with random bases: Pro et Contra

(2016) Alexander N. Gorban et al.   INFORMATION SCIENCES

Piece-wise quadratic approximations of arbitrary error functions for fast and robust machine learning

(2016) A.N. Gorban et al.   NEURAL NETWORKS

Fluorescence-based assay as a new screening tool for toxic chemicals

(2016) Ewa Moczko et al.   Scientific Reports

Rapid Encoding of New Memories by Individual Neurons in the Human Brain

(2015) Matias J. Ison et al.   NEURON

Data complexity measured by principal graphs

(2013) Andrei Zinovyev et al.   COMPUTERS & MATHEMATICS WITH APPLICATIONS

Is the k -NN classifier in high dimensions affected by the curse of dimensionality?

(2012) Vladimir Pestov   COMPUTERS & MATHEMATICS WITH APPLICATIONS

Concept cells: the building blocks of declarative memory functions

(2012) Rodrigo Quian Quiroga   NATURE REVIEWS NEUROSCIENCE

PRINCIPAL MANIFOLDS AND GRAPHS IN PRACTICE: FROM MOLECULAR BIOLOGY TO DYNAMICAL SYSTEMS

(2010) ALEXANDER N. GORBAN et al.   International Journal of Neural Systems

Human medial temporal lobe neurons respond preferentially to personally relevant images

(2009) Indre V. Viskontas et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA