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On the Use of A Priori Information for Sparse Signal Approximations

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Lasso (statistics)

In statistics and machine learning, lasso (least absolute shrinkage and selection operator; also Lasso or LASSO) is a regression analysis method that performs both variable selection and regularization in order to enhance the prediction accuracy and interpretability of the resulting statistical model. It was originally introduced in geophysics, and later by Robert Tibshirani, who coined the term. Lasso was originally formulated for linear regression models. This simple case reveals a substantial amount about the estimator.

Classical economics

Classical economics, classical political economy, or Smithian economics is a school of thought in political economy that flourished, primarily in Britain, in the late 18th and early-to-mid 19th century. Its main thinkers are held to be Adam Smith, Jean-Baptiste Say, David Ricardo, Thomas Robert Malthus, and John Stuart Mill. These economists produced a theory of market economies as largely self-regulating systems, governed by natural laws of production and exchange (famously captured by Adam Smith's metaphor of the invisible hand).

Classical liberalism

Classical liberalism is a political tradition and a branch of liberalism that advocates free market and laissez-faire economics; and civil liberties under the rule of law, with special emphasis on individual autonomy, limited government, economic freedom, political freedom and freedom of speech. Classical liberalism, contrary to liberal branches like social liberalism, looks more negatively on social policies, taxation and the state involvement in the lives of individuals, and it advocates deregulation.

Conjugate prior

In Bayesian probability theory, if the posterior distribution is in the same probability distribution family as the prior probability distribution , the prior and posterior are then called conjugate distributions, and the prior is called a conjugate prior for the likelihood function . A conjugate prior is an algebraic convenience, giving a closed-form expression for the posterior; otherwise, numerical integration may be necessary. Further, conjugate priors may give intuition by more transparently showing how a likelihood function updates a prior distribution.

Shift work sleep disorder

Shift work sleep disorder (SWSD) is a circadian rhythm sleep disorder characterized by insomnia, excessive sleepiness, or both affecting people whose work hours overlap with the typical sleep period. Insomnia can be the difficulty to fall asleep or to wake up before the individual has slept enough. About 20% of the working population participates in shift work. SWSD commonly goes undiagnosed, so it's estimated that 10–40% of shift workers have SWSD. The excessive sleepiness appears when the individual has to be productive, awake and alert.

Analytic–synthetic distinction

The analytic–synthetic distinction is a semantic distinction used primarily in philosophy to distinguish between propositions (in particular, statements that are affirmative subject–predicate judgments) that are of two types: analytic propositions and synthetic propositions. Analytic propositions are true or not true solely by virtue of their meaning, whereas synthetic propositions' truth, if any, derives from how their meaning relates to the world.

Information content

In information theory, the information content, self-information, surprisal, or Shannon information is a basic quantity derived from the probability of a particular event occurring from a random variable. It can be thought of as an alternative way of expressing probability, much like odds or log-odds, but which has particular mathematical advantages in the setting of information theory. The Shannon information can be interpreted as quantifying the level of "surprise" of a particular outcome.

Epistemology

Epistemology (ᵻˌpɪstəˈmɒlədʒi; ) is the branch of philosophy concerned with knowledge, and is considered a major subfield of philosophy, along with other major subfields such as ethics, logic, and metaphysics. Epistemologists study the nature, origin, and scope of knowledge, epistemic justification, the rationality of belief, and various related issues.

Feature learning

In machine learning, feature learning or representation learning is a set of techniques that allows a system to automatically discover the representations needed for feature detection or classification from raw data. This replaces manual feature engineering and allows a machine to both learn the features and use them to perform a specific task. Feature learning is motivated by the fact that machine learning tasks such as classification often require input that is mathematically and computationally convenient to process.

Mixture model

In statistics, a mixture model is a probabilistic model for representing the presence of subpopulations within an overall population, without requiring that an observed data set should identify the sub-population to which an individual observation belongs. Formally a mixture model corresponds to the mixture distribution that represents the probability distribution of observations in the overall population.