We wish to increase the power of an arbitrary algorithm designed for non-degenerate input, by allowing it to execute on all inputs. We concentrate on in nitesimal symbolic perturba...
Recently a bulk of research [14, 5, 15, 9] has been done on the modelling of the smallworld phenomenon, which has been shown to be pervasive in social and nature networks, and eng...
“The curse of dimensionality” is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and classification error in high dimension...
Mykola Pechenizkiy, Seppo Puuronen, Alexey Tsymbal
We reduce the problem of computing the rank and a nullspace basis of a univariate polynomial matrix to polynomial matrix multiplication. For an input n×n matrix of degree d over ...
Let p > 1 be any fixed real. We show that assuming NP RP, there is no polynomial time algorithm that approximates the Shortest Vector Problem (SVP) in p norm within a constant ...