Taylor's theoremIn calculus, Taylor's theorem gives an approximation of a -times differentiable function around a given point by a polynomial of degree , called the -th-order Taylor polynomial. For a smooth function, the Taylor polynomial is the truncation at the order of the Taylor series of the function. The first-order Taylor polynomial is the linear approximation of the function, and the second-order Taylor polynomial is often referred to as the quadratic approximation.
Gradient boostingGradient boosting is a machine learning technique used in regression and classification tasks, among others. It gives a prediction model in the form of an ensemble of weak prediction models, i.e., models that make very few assumptions about the data, which are typically simple decision trees. When a decision tree is the weak learner, the resulting algorithm is called gradient-boosted trees; it usually outperforms random forest.
Empirical risk minimizationEmpirical risk minimization (ERM) is a principle in statistical learning theory which defines a family of learning algorithms and is used to give theoretical bounds on their performance. The core idea is that we cannot know exactly how well an algorithm will work in practice (the true "risk") because we don't know the true distribution of data that the algorithm will work on, but we can instead measure its performance on a known set of training data (the "empirical" risk).
Brook TaylorBrook Taylor (18 August 1685 – 29 December 1731) was an English mathematician best known for creating Taylor's theorem and the Taylor series, which are important for their use in mathematical analysis. Brook Taylor was born in Edmonton (former Middlesex). Taylor was the son of John Taylor, MP of Patrixbourne, Kent and Olivia Tempest, the daughter of Sir Nicholas Tempest, Baronet of Durham. He entered St John's College, Cambridge, as a fellow-commoner in 1701, and took degrees in LL.B. in 1709 and LL.D. in 1714.
GradientIn vector calculus, the gradient of a scalar-valued differentiable function of several variables is the vector field (or vector-valued function) whose value at a point is the "direction and rate of fastest increase". If the gradient of a function is non-zero at a point , the direction of the gradient is the direction in which the function increases most quickly from , and the magnitude of the gradient is the rate of increase in that direction, the greatest absolute directional derivative.
Regularized least squaresRegularized least squares (RLS) is a family of methods for solving the least-squares problem while using regularization to further constrain the resulting solution. RLS is used for two main reasons. The first comes up when the number of variables in the linear system exceeds the number of observations. In such settings, the ordinary least-squares problem is ill-posed and is therefore impossible to fit because the associated optimization problem has infinitely many solutions.
Jus soliJus soli (dʒʌs_ˈsoʊlaɪ , juːs_ˈsoʊli ), commonly referred to as birthright citizenship, is the right to acquire nationality or citizenship by being born within the territory of a state. Jus soli was part of the English common law, in contrast to jus sanguinis, which derives from the Roman law that influenced the civil-law systems of mainland Europe.
Jus sanguinis(dʒʌs_ˈsæŋɡwɪnɪs , juːs_- , juːs ˈsaŋɡwɪnɪs; 'right of blood') is a principle of nationality law by which citizenship is determined or acquired by the nationality or ethnicity of one or both parents. Children at birth may be citizens of a particular state if either or both of their parents have citizenship of that state. It may also apply to national identities of ethnic, cultural, or other origins. Citizenship can also apply to children whose parents belong to a diaspora and were not themselves citizens of the state conferring citizenship.
Islamic StateThe Islamic State (IS), also known as the Islamic State of Iraq and the Levant (ISIL; ˈaɪsᵻl), Islamic State of Iraq and Syria (ISIS; ˈaɪsᵻs), and by its Arabic acronym Da'ish or Daesh (داعش, Dāʿish, ˈdaːʕɪʃ), is a transnational militant Islamist terrorist group and former unrecognized quasi-state that follows the Salafi jihadist branch of Sunni Islam. It was founded by Abu Musab al-Zarqawi in 1999 and gained global prominence in 2014, when it captured a large amount of Iraqi territory, and took advantage of the civil war in Syria to take control of chunks of territory in Eastern Syria.
Al-QaedaAl-Qaeda is a Sunni pan-Islamist militant organization led by Salafi jihadists who self-identify as a vanguard spearheading a global Islamist revolution to unite the Muslim world under a supra-national Islamic state known as the Caliphate. Its members are mostly composed of Arabs, but also include other peoples. Al-Qaeda has mounted attacks on civilian and military targets in various countries, including the 1998 United States embassy bombings and the September 11 attacks; it has been designated as a terrorist group by the United Nations Security Council, the North Atlantic Treaty Organization (NATO), the European Union, and various countries around the world.
Ridge regressionRidge regression is a method of estimating the coefficients of multiple-regression models in scenarios where the independent variables are highly correlated. It has been used in many fields including econometrics, chemistry, and engineering. Also known as Tikhonov regularization, named for Andrey Tikhonov, it is a method of regularization of ill-posed problems. It is particularly useful to mitigate the problem of multicollinearity in linear regression, which commonly occurs in models with large numbers of parameters.
Uniform convergenceIn the mathematical field of analysis, uniform convergence is a mode of convergence of functions stronger than pointwise convergence. A sequence of functions converges uniformly to a limiting function on a set as the function domain if, given any arbitrarily small positive number , a number can be found such that each of the functions differs from by no more than at every point in .
