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Probability Learning

Known as: Learning, Probability, Learnings, Probability, Probability Learnings 
Usually refers to the use of mathematical models in the prediction of learning to perform tasks based on the theory of probability applied to… Expand
National Institutes of Health

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Highly Cited
2011
Highly Cited
2011
A quantum probability model is introduced and used to explain human probability judgment errors including the conjunction and… Expand
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Highly Cited
2009
Highly Cited
2009
Probability theory has long been taken as the self-evident norm against which to evaluate inductive reasoning, and classical… Expand
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Highly Cited
2008
Highly Cited
2008
Quantum theory is a probabilistic theory with fixed causal structure. General relativity is a deterministic theory but where the… Expand
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Highly Cited
2006
Highly Cited
2006
We introduce a correspondence principle (analogous to the Furstenberg Correspondence Principle) that allows one to extract an… Expand
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Highly Cited
2001
Highly Cited
2001
The role of bromide in the formation and speciation of disinfection by-products (DBPs) during chlorination was investigated. The… Expand
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Highly Cited
2001
Highly Cited
2001
Abstract The renormalization group has played an important role in the physics of the second half of the 20th century both as a… Expand
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Highly Cited
1999
Highly Cited
1999
This major textbook from a distinguished econometrician is intended for students taking introductory courses in probability… Expand
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1995
1995
Contents §1. Introduction §2. The principle of the largest term 2.1. The general setting 2.2. The principle of the largest term 2… Expand
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Highly Cited
1989
Highly Cited
1989
We have employed Algorithmic Probability Theory to construct a system for machine learning of great power and generality. The… Expand
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Highly Cited
1987
Highly Cited
1987
Sun, 06 Jan 2019 10:24:00 GMT lectures on modern convex optimization pdf Convex optimization problems arise frequently in many… Expand
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