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Kolmogorov Structure Function
In 1973, Andrey Kolmogorov proposed a non-probabilistic approach to statistics and model selection. Let each datum be a finite binary string and a model be a finite set of binary strings. Consider model classes consisting of models of given maximal Kolmogorov complexity. The Kolmogorov structure function of an individual data string expresses the relation between the complexity level constraint on a model class and the least log-cardinality of a model in the class containing the data. The structure function determines all stochastic properties of the individual data string: for every constrained model class it determines the individual best-fitting model in the class irrespective of whether the true model is in the model class considered or not. In the classical case we talk about a set of data with a probability distribution, and the properties are those of the expectations. In contrast, here we deal with individual data strings and the properties of the individual string focused on. ...
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Andrey Kolmogorov
Andrey Nikolaevich Kolmogorov ( rus, Андре́й Никола́евич Колмого́ров, p=ɐnˈdrʲej nʲɪkɐˈlajɪvʲɪtɕ kəlmɐˈɡorəf, a=Ru-Andrey Nikolaevich Kolmogorov.ogg, 25 April 1903 – 20 October 1987) was a Soviet mathematician who contributed to the mathematics of probability theory, topology, intuitionistic logic, turbulence, classical mechanics, algorithmic information theory and computational complexity. Biography Early life Andrey Kolmogorov was born in Tambov, about 500 kilometers south-southeast of Moscow, in 1903. His unmarried mother, Maria Y. Kolmogorova, died giving birth to him. Andrey was raised by two of his aunts in Tunoshna (near Yaroslavl) at the estate of his grandfather, a well-to-do nobleman. Little is known about Andrey's father. He was supposedly named Nikolai Matveevich Kataev and had been an agronomist. Kataev had been exiled from St. Petersburg to the Yaroslavl province after his participation in the revolutionary mo ...
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Sufficient Statistic
In statistics, a statistic is ''sufficient'' with respect to a statistical model and its associated unknown parameter if "no other statistic that can be calculated from the same sample provides any additional information as to the value of the parameter". In particular, a statistic is sufficient for a family of probability distributions if the sample from which it is calculated gives no additional information than the statistic, as to which of those probability distributions is the sampling distribution. A related concept is that of linear sufficiency, which is weaker than ''sufficiency'' but can be applied in some cases where there is no sufficient statistic, although it is restricted to linear estimators. The Kolmogorov structure function deals with individual finite data; the related notion there is the algorithmic sufficient statistic. The concept is due to Sir Ronald Fisher in 1920. Stephen Stigler noted in 1973 that the concept of sufficiency had fallen out of favor in de ...
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Rate Distortion
Rate or rates may refer to: Finance * Rates (tax), a type of taxation system in the United Kingdom used to fund local government * Exchange rate, rate at which one currency will be exchanged for another Mathematics and science * Rate (mathematics), a specific kind of ratio, in which two measurements are related to each other (often with respect to time) * Rate function, a function used to quantify the probabilities of a rare event * Reaction rate, in chemistry the speed at which reactants are converted into products Military * Naval rate, a junior enlisted member of a navy * Rating system of the Royal Navy, a former method of indicating a British warship's firepower People * Ed Rate (1899–1990), American football player * José Carlos Rates (1879–1945), General Secretary of the Portuguese Communist Party * Peter of Rates (died 60 AD), traditionally considered to be the first bishop of Braga Other uses * Rate (building), the class of a building in late Georgian a ...
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Maximum Likelihood
In statistics, maximum likelihood estimation (MLE) is a method of estimating the parameters of an assumed probability distribution, given some observed data. This is achieved by maximizing a likelihood function so that, under the assumed statistical model, the observed data is most probable. The point in the parameter space that maximizes the likelihood function is called the maximum likelihood estimate. The logic of maximum likelihood is both intuitive and flexible, and as such the method has become a dominant means of statistical inference. If the likelihood function is differentiable, the derivative test for finding maxima can be applied. In some cases, the first-order conditions of the likelihood function can be solved analytically; for instance, the ordinary least squares estimator for a linear regression model maximizes the likelihood when all observed outcomes are assumed to have Normal distributions with the same variance. From the perspective of Bayesian infere ...
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Jorma Rissanen
Jorma Johannes Rissanen (October 20, 1932 – May 9, 2020) was an information theorist, known for originating the minimum description length (MDL) principle and practical approaches to arithmetic coding for lossless data compression. His work inspired the development of the theory of stochastic chains with memory of variable length. Education and career Rissanen was born in Pielisjärvi (now Lieksa in Finland and grew up in Kemi, a border town between Finland and Sweden. He moved to Helsinki and studied at the Helsinki University of Technology, where he obtained his Master’s degree in electrical engineering in 1956 and licentiate in control theory in 1960. He studied there under Olli Lokki and Hans Blomberg. Rissanen became an IBM researcher since 1960, first in Stockholm, Sweden, while still a Ph.D. student under Hans Blomberg. Most of his PhD work was done remotely as a result and he received his Ph.D. from the Helsinki University of Technology in 1965 with a topic on ...
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Minimum Description Length
Minimum Description Length (MDL) is a model selection principle where the shortest description of the data is the best model. MDL methods learn through a data compression perspective and are sometimes described as mathematical applications of Occam's razor. The MDL principle can be extended to other forms of inductive inference and learning, for example to estimation and sequential prediction, without explicitly identifying a single model of the data. MDL has its origins mostly in information theory and has been further developed within the general fields of statistics, theoretical computer science and machine learning, and more narrowly computational learning theory. Historically, there are different, yet interrelated, usages of the definite noun phrase "''the'' minimum description length ''principle''" that vary in what is meant by ''description'': * Within Jorma Rissanen's theory of learning, a central concept of information theory, models are statistical hypotheses and descr ...
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Minimal Sufficient Statistic
Minimal may refer to: * Minimal (music genre), art music that employs limited or minimal musical materials * "Minimal" (song), 2006 song by Pet Shop Boys * Minimal (supermarket) or miniMAL, a former supermarket chain in Germany and Poland * Minimal (''Dungeons & Dragons''), a creature of magically reduced size in the game ''Dungeons & Dragons'' * Minimal (chocolate), a bean to bar chocolate store in Japan, featured in '' Kantaro: The Sweet Tooth Salaryman'' * Minimal (clothing), an Indonesia clothing-retail company that worked with fashion model Ayu Gani See also * *Minimalism (other) *Maximal (other) *Minimisation (other) Minimisation or minimization may refer to: * Minimisation (psychology), downplaying the significance of an event or emotion * Minimisation (clinical trials) * Minimisation (code) or Minification, removing unnecessary characters from source code ... * Minimal prime (other) {{disambiguation ...
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Estimator
In statistics, an estimator is a rule for calculating an estimate of a given quantity based on observed data: thus the rule (the estimator), the quantity of interest (the estimand) and its result (the estimate) are distinguished. For example, the sample mean is a commonly used estimator of the population mean. There are point and interval estimators. The point estimators yield single-valued results. This is in contrast to an interval estimator, where the result would be a range of plausible values. "Single value" does not necessarily mean "single number", but includes vector valued or function valued estimators. ''Estimation theory'' is concerned with the properties of estimators; that is, with defining properties that can be used to compare different estimators (different rules for creating estimates) for the same quantity, based on the same data. Such properties can be used to determine the best rules to use under given circumstances. However, in robust statistics, statis ...
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Paul Vitányi
Paul Michael Béla Vitányi (born 21 July 1944) is a Dutch computer scientist, Professor of Computer Science at the University of Amsterdam and researcher at the Dutch Centrum Wiskunde & Informatica. Biography Vitányi was born in Budapest to a Dutch mother and a Hungarian father. He received his degree of mathematical engineer from Delft University of Technology in 1971 and his Ph.D. from the Free University of Amsterdam in 1978.. Career Vitányi was appointed professor of computer science at the University of Amsterdam, and researcher at the National Research Institute for Mathematics and Computer Science in the Netherlands ( CWI) where he is currently a CWI Fellow. He was guest professor at the University of Copenhagen in 1978; research associate at the Massachusetts Institute of Technology in 1985/1986; Gaikoku-Jin Kenkyuin (councellor professor) at INCOCSAT at the Tokyo Institute of Technology in 1998; visiting professor at Boston University in 2004, at Monash University in ...
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Kolmogorov Complexity
In algorithmic information theory (a subfield of computer science and mathematics), the Kolmogorov complexity of an object, such as a piece of text, is the length of a shortest computer program (in a predetermined programming language) that produces the object as output. It is a measure of the computational resources needed to specify the object, and is also known as algorithmic complexity, Solomonoff–Kolmogorov–Chaitin complexity, program-size complexity, descriptive complexity, or algorithmic entropy. It is named after Andrey Kolmogorov, who first published on the subject in 1963 and is a generalization of classical information theory. The notion of Kolmogorov complexity can be used to state and prove impossibility results akin to Cantor's diagonal argument, Gödel's incompleteness theorem, and Turing's halting problem. In particular, no program ''P'' computing a lower bound for each text's Kolmogorov complexity can return a value essentially larger than ''P'''s own len ...
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Kolmogorov
Andrey Nikolaevich Kolmogorov ( rus, Андре́й Никола́евич Колмого́ров, p=ɐnˈdrʲej nʲɪkɐˈlajɪvʲɪtɕ kəlmɐˈɡorəf, a=Ru-Andrey Nikolaevich Kolmogorov.ogg, 25 April 1903 – 20 October 1987) was a Soviet mathematician who contributed to the mathematics of probability theory, topology, intuitionistic logic, turbulence, classical mechanics, algorithmic information theory and computational complexity. Biography Early life Andrey Kolmogorov was born in Tambov, about 500 kilometers south-southeast of Moscow, in 1903. His unmarried mother, Maria Y. Kolmogorova, died giving birth to him. Andrey was raised by two of his aunts in Tunoshna (near Yaroslavl) at the estate of his grandfather, a well-to-do nobleman. Little is known about Andrey's father. He was supposedly named Nikolai Matveevich Kataev and had been an agronomist. Kataev had been exiled from St. Petersburg to the Yaroslavl province after his participation in the revolutionary mov ...
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Kolm Complexity Lect
KOLM (1520 AM, "1520 The Ticket") is a sports formatted radio station in Rochester, Minnesota, and is owned by Townsquare Media. KOLM derives a portion of its programming from CBS Sports Radio. On August 30, 2013, a deal was announced in which Townsquare would acquire 53 Cumulus Media stations, including KOLM, for $238 million. The deal is part of Cumulus' acquisition of Dial Global Westwood One is an American radio network owned by Cumulus Media. The company syndicates talk, music, and sports programming. The company takes its name from an earlier network also named Westwood One, a company founded in 1978. The company ...; Townsquare and Dial Global are both controlled by Oaktree Capital Management. The sale to Townsquare was completed on November 14, 2013. References External linksKOLM official website Radio stations in Minnesota Radio stations established in 1959 CBS Sports Radio stations Townsquare Media radio stations 1959 establishments in Minnesota
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