Artificial intelligence and data

Applicant tracking system

An applicant tracking system (ATS) is software that collects, organizes, and screens job applications, from job posting through interview scheduling and hiring, used by 99% of Fortune 500 companies.

Applications of artificial intelligence

Applications of AI are the practical uses of machine learning across sectors like healthcare, energy, and agriculture, analyzing large datasets to detect patterns, support decisions, and automate operations.

Apprenticeship learning

Apprenticeship learning is a reinforcement learning method that learns a near-expert policy from expert demonstrations when no reward function is given, used in tasks like driving and autonomous helicopter flight.

Approximate dynamic programming

Approximate dynamic programming (ADP) is a family of computational methods that approximate value functions in large-scale decision problems where exact dynamic programming is intractable, known in other fields as neuro-dynamic programming and reinforcement learning.

Approximate inference

Approximate inference is the class of computational methods that estimate a Bayesian posterior distribution when exact computation is intractable, chiefly Markov chain Monte Carlo and variational inference.

Approximate nearest neighbor search

Approximate nearest neighbor (ANN) search is a family of algorithms that quickly finds points near a query in high-dimensional spaces, trading a small loss of exactness for speed.

Approximate reasoning

Approximate reasoning is a framework in artificial intelligence and logic that draws conclusions from imprecise or vague information, formalized by Lotfi Zadeh through fuzzy sets.

Approximate string matching

Approximate string matching, also known as fuzzy string searching, finds all text locations matching a pattern within k edits, and underlies spellcheckers and DNA read mapping.

Approximation

Approximation in numerical mathematics replaces an exact mathematical object, such as a function or number, by a simpler computable one, together with a measure of its error.

Approximation algorithm

An approximation algorithm is a polynomial-time algorithm for an NP-hard optimization problem that guarantees its solution stays within a provable factor of the optimum on every input.

Apriori algorithm

The Apriori algorithm is a data mining algorithm for finding frequent itemsets and association rules in transaction databases, proposed by Rakes Agrawal and Ramakrishnan Srikant in 1994.

APX

APX, short for approximable, is a complexity class of NP optimization problems with polynomial-time constant-factor approximation algorithms, including vertex cover and MAX-3SAT; a PTAS for any APX-hard problem would imply P = NP.

ArangoDB

ArangoDB is a multi-model database system, written in C++ and developed by ArangoDB GmbH in Cologne since 2014, unifying graph, document, and key-value models under one query language, AQL.

Arc consistency

Arc consistency is a local consistency property of constraint satisfaction problems: each value in one variable's domain must have support in the other, formalized by Alan Mackworth in 1977.

Arg max

Arg max, also known as the argument of the maximum or written argmax, returns the inputs where a function attains its maximum value, not the value itself.