Nouvelles méthodes pour la détermination des orbites des comètes

By A. Legendre. 1970

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Citations in the corpus

Revisiting Stein's paradox: multi-task averaging (2014, background): “Legendre (1805) noted that the mean minimizes the sum of squared errors to a set of samples: ȳ = arg min ỹ N∑ i=1 (yi − ỹ)2.”
An Update on the Hirsch Conjecture (2009, background): “In the same vein, Eisenbrand, Hähnle, Razborov and Rothvoß [24] have recently shown the following generalization of Theorems 2.”
A comprehensive survey on machine learning for networking: evolution, applications and research opportunities (2018, methodology): “In the 1950s, the simplest linear regression model called Ordinary Least Squares (OLS) –derived from the least squares method [266, 423] developed around the 1800s– was used to calculate linear regressions in electromechanical desk calculators [168].”
Interpretable Machine Learning - A Brief History, State-of-the-Art and Challenges (2020, methodology): “Linear regression models were used by Gauss, Legendre, and Quetelet [109,64,37,90] as early as the beginning of the 19th century and have since then grown into a vast array of regression analysis tools [115,98], for example, generalized additive models [45] and elastic net [132].”
Kalman-Based Stochastic Gradient Method with Stop Condition and Insensitivity to Conditioning (2015, background): “Informally, the linear regression problem is the task of determining β ∗ from the data ( X 1 , Y 1 ) , ( X 2 , Y 2 ) , . . . .”
Integrating generic sensor fusion algorithms with sound state representations through encapsulation of manifolds (2011, methodology): “t Squares Optimization Least squares optimization dates back to the late 18th century where it was used to combine measurements in astronomy and in geodesy. Initial publications were made by Legendre [29] and Gauss [12] in the early 19th century. The method 9 Classical Gauss-Newton Gauss-Newton on a”
Foundations of Linear and Generalized Linear Models (2015, background): “For this reason, least squares has a long history, dating back to a published article by the French mathematician Adrien-Marie Legendre (1805),”