54 relations: Aalto University, Alan Turing, Aleksandr Gorban, Approximation error, Artificial neural network, Backpropagation, Bootstrapping (statistics), Cerebral cortex, Competitive learning, Deep learning, Dimensionality reduction, Eigenvalues and eigenvectors, Elastic energy, Elastic map, Emergence, Euclidean distance, Feedforward neural network, Finland, Gaussian function, Generative topographic map, Gradient descent, Growing self-organizing map, Hexagon, Human brain, Hybrid Kohonen self-organizing map, International Journal of Neural Systems, Iris flower data set, K-means clustering, Learning vector quantization, Least squares, Liquid state machine, Monotonic function, Moore neighborhood, Morphogenesis, Multidimensional scaling, Neocognitron, Neural coding, Neural gas, Principal component analysis, Rectangle, Scientific visualization, Sense, Sparse distributed memory, Spline interpolation, Teuvo Kohonen, Topological data analysis, Topology, Torus, U-matrix, Unit cube, ..., Unit vector, Unsupervised learning, Vector quantization, Von Neumann neighborhood. Expand index (4 more) » « Shrink index
Aalto University (Aalto-yliopisto, Aalto-universitetet) is a university primarily located in Greater Helsinki, Finland.
Alan Mathison Turing (23 June 1912 – 7 June 1954) was an English computer scientist, mathematician, logician, cryptanalyst, philosopher, and theoretical biologist.
Alexander Nikolaevich Gorban (Александр Николаевич Горба́нь.) is a scientist of Soviet origin, working in the United Kingdom.
The approximation error in some data is the discrepancy between an exact value and some approximation to it.
Artificial neural networks (ANNs) or connectionist systems are computing systems vaguely inspired by the biological neural networks that constitute animal brains.
Backpropagation is a method used in artificial neural networks to calculate a gradient that is needed in the calculation of the weights to be used in the network.
In statistics, bootstrapping is any test or metric that relies on random sampling with replacement.
The cerebral cortex is the largest region of the cerebrum in the mammalian brain and plays a key role in memory, attention, perception, cognition, awareness, thought, language, and consciousness.
Competitive learning is a form of unsupervised learning in artificial neural networks, in which nodes compete for the right to respond to a subset of the input data.
Deep learning (also known as deep structured learning or hierarchical learning) is part of a broader family of machine learning methods based on learning data representations, as opposed to task-specific algorithms.
In statistics, machine learning, and information theory, dimensionality reduction or dimension reduction is the process of reducing the number of random variables under consideration by obtaining a set of principal variables.
In linear algebra, an eigenvector or characteristic vector of a linear transformation is a non-zero vector that changes by only a scalar factor when that linear transformation is applied to it.
Elastic energy is the potential mechanical energy stored in the configuration of a material or physical system as work is performed to distort its volume or shape.
Elastic maps provide a tool for nonlinear dimensionality reduction.
In philosophy, systems theory, science, and art, emergence occurs when "the whole is greater than the sum of the parts," meaning the whole has properties its parts do not have.
In mathematics, the Euclidean distance or Euclidean metric is the "ordinary" straight-line distance between two points in Euclidean space.
A feedforward neural network is an artificial neural network wherein connections between the nodes do not form a cycle.
Finland (Suomi; Finland), officially the Republic of Finland is a country in Northern Europe bordering the Baltic Sea, Gulf of Bothnia, and Gulf of Finland, between Norway to the north, Sweden to the northwest, and Russia to the east.
In mathematics, a Gaussian function, often simply referred to as a Gaussian, is a function of the form: for arbitrary real constants, and.
Generative topographic map (GTM) is a machine learning method that is a probabilistic counterpart of the self-organizing map (SOM), is probably convergent and does not require a shrinking neighborhood or a decreasing step size.
Gradient descent is a first-order iterative optimization algorithm for finding the minimum of a function.
A growing self-organizing map (GSOM) is a growing variant of a self-organizing map (SOM).
In geometry, a hexagon (from Greek ἕξ hex, "six" and γωνία, gonía, "corner, angle") is a six-sided polygon or 6-gon.
The human brain is the central organ of the human nervous system, and with the spinal cord makes up the central nervous system.
In artificial neural networks, a hybrid Kohonen self-organizing map is a type of self-organizing map (SOM) named for the Finnish professor Teuvo Kohonen, where the network architecture consists of an input layer fully connected to a 2–D SOM or Kohonen layer.
The International Journal of Neural Systems is a bimonthly peer-reviewed scientific journal founded in 1989.
The Iris flower data set or Fisher's Iris data set is a multivariate data set introduced by the British statistician and biologist Ronald Fisher in his 1936 paper The use of multiple measurements in taxonomic problems as an example of linear discriminant analysis.
k-means clustering is a method of vector quantization, originally from signal processing, that is popular for cluster analysis in data mining.
In computer science, learning vector quantization (LVQ), is a prototype-based supervised classification algorithm.
The method of least squares is a standard approach in regression analysis to approximate the solution of overdetermined systems, i.e., sets of equations in which there are more equations than unknowns.
A liquid state machine (LSM) is a particular kind of spiking neural network.
In mathematics, a monotonic function (or monotone function) is a function between ordered sets that preserves or reverses the given order.
In cellular automata, the Moore neighborhood is defined on a two-dimensional square lattice and is composed of a central cell and the eight cells which surround it.
Morphogenesis (from the Greek morphê shape and genesis creation, literally, "beginning of the shape") is the biological process that causes an organism to develop its shape.
Multidimensional scaling (MDS) is a means of visualizing the level of similarity of individual cases of a dataset.
The neocognitron is a hierarchical, multilayered artificial neural network proposed by Kunihiko Fukushima in the 1980s.
Neural coding is a neuroscience field concerned with characterising the hypothetical relationship between the stimulus and the individual or ensemble neuronal responses and the relationship among the electrical activity of the neurons in the ensemble.
Neural gas is an artificial neural network, inspired by the self-organizing map and introduced in 1991 by Thomas Martinetz and Klaus Schulten.
Principal component analysis (PCA) is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components.
In Euclidean plane geometry, a rectangle is a quadrilateral with four right angles.
Scientific visualization (also spelled scientific visualisation) is an interdisciplinary branch of science.
A sense is a physiological capacity of organisms that provides data for perception.
Sparse distributed memory (SDM) is a mathematical model of human long-term memory introduced by Pentti Kanerva in 1988 while he was at NASA Ames Research Center.
In the mathematical field of numerical analysis, Spline interpolation is a form of interpolation where the interpolant is a special type of piecewise polynomial called a spline.
Teuvo Kalevi Kohonen (born July 11, 1934) is a prominent Finnish academic (Dr. Eng.) and researcher.
In applied mathematics, topological data analysis (TDA) is an approach to the analysis of datasets using techniques from topology.
In mathematics, topology (from the Greek τόπος, place, and λόγος, study) is concerned with the properties of space that are preserved under continuous deformations, such as stretching, crumpling and bending, but not tearing or gluing.
In geometry, a torus (plural tori) is a surface of revolution generated by revolving a circle in three-dimensional space about an axis coplanar with the circle.
The U-matrix (unified distance matrix) is a representation of a self-organizing map (SOM) where the Euclidean distance between the codebook vectors of neighboring neurons is depicted in a grayscale image.
A unit cube, more formally a cube of side 1, is a cube whose sides are 1 unit long.
In mathematics, a unit vector in a normed vector space is a vector (often a spatial vector) of length 1.
Unsupervised machine learning is the machine learning task of inferring a function that describes the structure of "unlabeled" data (i.e. data that has not been classified or categorized).
Vector quantization (VQ) is a classical quantization technique from signal processing that allows the modeling of probability density functions by the distribution of prototype vectors.
In cellular automata, the von Neumann neighborhood is classically defined on a two-dimensional square lattice and is composed of a central cell and its four adjacent cells.
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