error probability bound
31BPL (complexity) — In computational complexity theory, BPL (Bounded error Probabilistic Logarithmic space), [ [http://qwiki.stanford.edu/wiki/Complexity Zoo:B#bpl Complexity Zoo: BPL] ] sometimes called BPLP (Bounded error Probabilistic Logarithmic space Polynomial …
32Set cover problem — The set covering problem is a classical question in computer science and complexity theory. As input you are given several sets. They may have some elements in common. You must select a minimum number of these sets so that the sets you have… …
33Abkürzungen/Luftfahrt/B–D — Dies ist der zweite Teil der Liste Abkürzungen/Luftfahrt. Liste der Abkürzungen Teil 1 A A Teil 2 B–D B (BA, BB, BC, BD, BE, BF, BG, BH, BI, BJ, BK, BL …
34Almost Wide Probabilistic Polynomial-Time — In theoretical computer science, Almost Wide Probabilistic Polynomial Time (AWPP) is a complexity class for problems in the context of quantum computing.AWPP contains the BQP (Bounded error, Quantum, Polynomial time) class, which contains the… …
35Feature selection — Feature selection, also known as variable selection, feature reduction, attribute selection or variable subset selection, is the technique, commonly used in machine learning, of selecting a subset of relevant features for building robust learning …
36Mathematics and Physical Sciences — ▪ 2003 Introduction Mathematics Mathematics in 2002 was marked by two discoveries in number theory. The first may have practical implications; the second satisfied a 150 year old curiosity. Computer scientist Manindra Agrawal of the… …
37Common Lisp — Paradigm(s) Multi paradigm: procedural, functional, object oriented, meta, reflective, generic Appeared in 1984, 1994 for ANSI Common Lisp Developer ANSI X3J13 committee Typing discipline …
38Normal distribution — This article is about the univariate normal distribution. For normally distributed vectors, see Multivariate normal distribution. Probability density function The red line is the standard normal distribution Cumulative distribution function …
39Estimation theory — is a branch of statistics and signal processing that deals with estimating the values of parameters based on measured/empirical data. The parameters describe an underlying physical setting in such a way that the value of the parameters affects… …
40Decision tree model — In computational complexity and communication complexity theories the decision tree model is the model of computation or communication in which an algorithm or communication process is considered to be basically a decision tree, i.e., a sequence… …
