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Grokking (machine Learning)
In machine learning, grokking, or delayed generalization, is a transition to generalization that occurs many training iterations after the interpolation threshold, after many iterations of seemingly little progress, as opposed to the usual process where generalization occurs slowly and progressively once the interpolation threshold has been reached. The term derives from the word ''grok'' coined by Robert Heinlein in his novel ''Stranger in a Strange Land''. Grokking can be understood as a phase transition In chemistry, thermodynamics, and other related fields, a phase transition (or phase change) is the physical process of transition between one state of a medium and another. Commonly the term is used to refer to changes among the basic states ... during the training process. While grokking has been thought of as largely a phenomenon of relatively shallow models, grokking has been observed in deep neural networks and non-neural models and is the subject of active research ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Machine Learning
Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so. Machine learning algorithms are used in a wide variety of applications, such as in medicine, email filtering, speech recognition, agriculture, and computer vision, where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks.Hu, J.; Niu, H.; Carrasco, J.; Lennox, B.; Arvin, F.,Voronoi-Based Multi-Robot Autonomous Exploration in Unknown Environments via Deep Reinforcement Learning IEEE Transactions on Vehicular Technology, 2020. A subset of machine learning is closely related to computational statistics, which focuses on making pred ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Generalization (learning)
Generalization is the concept that humans and other animals use past learning in present situations of learning if the conditions in the situations are regarded as similar. The learner uses generalized patterns, principles, and other similarities between past experiences and novel experiences to more efficiently navigate the world.Banich, M. T., Dukes, P., & Caccamise, D. (2010). Generalization of knowledge: Multidisciplinary perspectives. Psychology Press. For example, if a person has learned in the past that every time they eat an apple, their throat becomes itchy and swollen, they might assume they are allergic to all fruit. When this person is offered a banana to eat, they reject it upon assuming they are also allergic to it through generalizing that all fruits cause the same reaction. Although this generalization about being allergic to all fruit based on experiences with one fruit could be correct in some cases, it may not be correct in all. Both positive and negative effects h ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Interpolation Threshold
In statistics and machine learning, double descent is the phenomenon where a statistical model with a small number of parameters and a model with an extremely large number of parameters have a small error, but a model whose number of parameters is about the same as the number of data points used to train the model will have a large error. This phenomenon seems to contradict the bias-variance tradeoff in classical statistics, which states that having too many parameters will yield an extremely large error. See also * Bias–variance tradeoff In statistics and machine learning, the bias–variance tradeoff is the property of a model that the variance of the parameter estimated across samples can be reduced by increasing the bias in the estimated parameters. The bias–variance d ... References * * * * * * External links * * Model selection Machine learning Statistical classification {{stat-stub ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Grok
''Grok'' is a neologism coined by American writer Robert A. Heinlein for his 1961 science fiction novel ''Stranger in a Strange Land''. While the ''Oxford English Dictionary'' summarizes the meaning of ''grok'' as "to understand intuitively or by empathy, to establish rapport with" and "to empathize or communicate sympathetically (with); also, to experience enjoyment", Heinlein's concept is far more nuanced, with critic Istvan Csicsery-Ronay Jr. observing that "the book's major theme can be seen as an extended definition of the term." The concept of ''grok'' garnered significant critical scrutiny in the years after the book's initial publication. The term and aspects of the underlying concept have become part of communities such as computer science. Descriptions of ''grok'' in ''Stranger in a Strange Land'' Critic David E. Wright Sr. points out that in the 1991 "uncut" edition of ''Stranger'', the word ''grok'' "was used first ''without any explicit definition'' on page 22" and ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Stranger In A Strange Land
''Stranger in a Strange Land'' is a 1961 science fiction novel by American author Robert A. Heinlein. It tells the story of Valentine Michael Smith, a human who comes to Earth in early adulthood after being born on the planet Mars and raised by Martians, and explores his interaction with and eventual transformation of Terran culture. The title "Stranger in a Strange Land" is a direct quotation from the King James Bible (taken from Exodus 2:22). The working title for the book was "A Martian Named Smith", which was also the name of the screenplay started by a character at the end of the novel. Heinlein's widow Virginia arranged to have the original unedited manuscript published in 1991, three years after Heinlein's death. Critics disagree about which version is superior. ''Stranger in a Strange Land'' won the 1962 Hugo Award for Best Novel and became the first science fiction novel to enter ''The New York Times Book Review'''s best-seller list. In 2012, the Library of Congress n ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Phase Transition
In chemistry, thermodynamics, and other related fields, a phase transition (or phase change) is the physical process of transition between one state of a medium and another. Commonly the term is used to refer to changes among the basic states of matter: solid, liquid, and gas, and in rare cases, plasma. A phase of a thermodynamic system and the states of matter have uniform physical properties. During a phase transition of a given medium, certain properties of the medium change as a result of the change of external conditions, such as temperature or pressure. This can be a discontinuous change; for example, a liquid may become gas upon heating to its boiling point, resulting in an abrupt change in volume. The identification of the external conditions at which a transformation occurs defines the phase transition point. Types of phase transition At the phase transition point for a substance, for instance the boiling point, the two phases involved - liquid and vapor, have ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Deep Double Descent
In statistics and machine learning, double descent is the phenomenon where a statistical model with a small number of parameters and a model with an extremely large number of parameters have a small error, but a model whose number of parameters is about the same as the number of data points used to train the model will have a large error. This phenomenon seems to contradict the bias-variance tradeoff in classical statistics, which states that having too many parameters will yield an extremely large error. See also * Bias–variance tradeoff In statistics and machine learning, the bias–variance tradeoff is the property of a model that the variance of the parameter estimated across samples can be reduced by increasing the bias in the estimated parameters. The bias–variance d ... References * * * * * * External links * * Model selection Machine learning Statistical classification {{stat-stub ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Machine Learning
Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so. Machine learning algorithms are used in a wide variety of applications, such as in medicine, email filtering, speech recognition, agriculture, and computer vision, where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks.Hu, J.; Niu, H.; Carrasco, J.; Lennox, B.; Arvin, F.,Voronoi-Based Multi-Robot Autonomous Exploration in Unknown Environments via Deep Reinforcement Learning IEEE Transactions on Vehicular Technology, 2020. A subset of machine learning is closely related to computational statistics, which focuses on making pred ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
