science, k-approximation of k-hitting set is an approximation algorithm for weighted hitting set. The input is a collection S of subsets of some universe...

problem is equivalent to the hitting set problem. A subset H {\displaystyle H} of U {\displaystyle U} is called a hitting set when H ∩ S j ≠ ∅ {\displaystyle...

the geometric nature, the approximation ratios for these problems can be much better than the general set cover/hitting set problems. Moreover, these...

= k ) = ( n k ) p k ( 1 − p ) n − k {\displaystyle f(k,n,p)=\Pr(X=k)={\binom {n}{k}}p^{k}(1-p)^{n-k}} for k = 0, 1, 2, ..., n, where ( n k ) = n ! k !...

successive approximation: β j k + 1 = β j k + Δ β j , {\displaystyle {\beta _{j}}^{k+1}={\beta _{j}}^{k}+\Delta \beta _{j},} where a superscript k is an iteration...

= k 1 , X 2 = k 2 ) = exp ⁡ ( − λ 1 − λ 2 − λ 3 ) λ 1 k 1 k 1 ! λ 2 k 2 k 2 ! ∑ k = 0 min ( k 1 , k 2 ) ( k 1 k ) ( k 2 k ) k ! ( λ 3 λ 1 λ 2 ) k {\displaystyle...

result of the good approximation that an event with ⁠1/k⁠ probability will have a ⁠1/2⁠ chance of occurring at least once if it is repeated k ln 2 times...

approximation (i.e., which holds as m →∞). Second, of more concern, it assumes that during the membership test the event that one tested bit is set to...

the study of Diophantine approximation deals with the approximation of real numbers by rational numbers. It is named after Diophantus of Alexandria....

method Column generation k-approximation of k-hitting set — algorithm for specific LP problems (to find a weighted hitting set) Linear complementarity...

best rank‑k approximation to P in the least‑squares (Frobenius‑norm) sense is P k = U k Σ k V k T {\displaystyle P_{k}=U_{k}\,\Sigma _{k}\,V_{k}^{T}} ,...

polynomial time, the minimum feedback arc set can be approximated to within a polylogarithmic approximation ratio, and maximum acyclic subgraphs can be...

y k | x k ) p ( x k | x k − 1 ) d x k p ( x k | x k − 1 ) d x k ≃ N ↑ ∞ p ( y k | x k ) ∫ p ( y k | x k ) p ^ ( d x k | x k − 1 ) p ^ ( d x k | x k −...

about what it means to say of a person that they speak Japanese is that the person knows, at least to some approximation, how to structure linguistic...

final result, the approximation of π. There are two important considerations: If the points are not uniformly distributed, the approximation will be poor....

vector k = ( k x , k y , k z ) {\displaystyle \mathbf {k} =(k_{x},k_{y},k_{z})} and define l x = k x | k | , l y = k y | k | , l z = k z | k | {\displaystyle...

Manoban is a better approximation of the Thai pronunciation and is the spelling recommended by the Royal Thai General System of Transcription. Thai pronunciation:...

the case that such approximations are less accurate in the tails of the distribution. A general upper bound for the approximation error in the central...

given by p X ( k ) = Pr ( X = k ) = ( K k ) ( N − K n − k ) ( N n ) , {\displaystyle p_{X}(k)=\Pr(X=k)={\frac {{\binom {K}{k}}{\binom {N-K}{n-k}}}{\binom {N}{n}}}...

do not compute all ways of splitting the original sample. These methods are approximations of leave-p-out cross-validation. In k-fold cross-validation,...

Normal approximation by Stein's method. Springer. ISBN 978-3-642-15006-7. Artstein, S.; Ball, K.; Barthe, F.; Naor, A. (2004). "Solution of Shannon's...

Stochastic approximation methods are a family of iterative methods typically used for root-finding problems or for optimization problems. The recursive...

by w k / W k {\displaystyle w_{k}/W_{k}} : A 0 = 0 A k = A k − 1 + w k W k ( x k − A k − 1 ) Q 0 = 0 Q k = Q k − 1 + w k W k − 1 W k ( x k − A k − 1 )...

Rajaraman & J. Ullman (2010). "Mining of Massive Datasets, Ch. 3". Weber, Roger; Blott, Stephen. "An Approximation-Based Data Structure for Similarity Search"...

can be assessed because we know Ĵ. If Ĵ is a reasonable approximation to J, then the quality of inference on J can in turn be inferred. As an example,...

implemented in the critical path of computer systems, such as operating systems, due to its high overhead; Clock, an approximation of LRU, is commonly used instead...

generalizations of interpolation splines where the functions are determined to minimize a weighted combination of the average squared approximation error over...

In statistics, first-hitting-time models are simplified models that estimate the amount of time that passes before some random or stochastic process crosses...

In statistical modeling, regression analysis is a set of statistical processes for estimating the relationships between a dependent variable (often called...

constant interval lengths: m k = 1 2 ( p k + 1 − p k x k + 1 − x k + p k − p k − 1 x k − x k − 1 ) {\displaystyle {\boldsymbol {m}}_{k}={\frac {1}{2}}\left({\frac...