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Paweł Siedlecki

Publications and source records attributed to Paweł Siedlecki.

3 recordsLinked to original sources

Information-Based Complexity vs Computational Complexity in Phaseless Polynomial Interpolation

The authors of ``A note on the complexity of a phaseless polynomial interpolation'' have shown that phaseless polynomial interpolation over $\mathbf{Q}$ is possible with $n+2$ points, where $n$ is the upper-bound on the degree of a polynomial. Nonetheless, their reconstruction algorithm and the method of adaptively choosing evaluation points are exponential time. On the other hand, they have also shown that given $2n+1$ points, the polynomial can be reconstructed in a polynomial time. A conjecture have been put forward, namely that the reconstruction problem from such $n+2$ points is exponential time. Moreover, a question about the number of points sufficient for polynomial time reconstruction have been posed. In this paper, we answer these questions -- we show that (1) reconstruction problem from $2n-k$ for any constant $k$ is polynomial time, (2) reconstruction problem from $(1+c)n+2$ points for any constant $c \in [0, 1)$ is NP-Complete, (3) evaluation points admitting a unique solution can be chosen in polynomial time.

cs.CC↗

Worst case tractability of linear problems in the presence of noise: linear information

We study the worst case tractability of multivariate linear problems defined on separable Hilbert spaces. Information about a problem instance consists of noisy evaluations of arbitrary bounded linear functionals, where the noise is either deterministic or random. The cost of a single evaluation depends on its precision and is controlled by a cost function. We establish mutual interactions between tractability of a problem with noisy information, the cost function, and tractability of the same problem, but with exact information.

math.NA↗

Notes on $(s,t)$-weak tractability: A refined classification of problems with (sub)exponential information complexity

In the last 20 years a whole hierarchy of notions of tractability was proposed and analyzed by several authors. These notions are used to classify the computational hardness of continuous numerical problems $S=(S_d)_{d\in\mathbb{N}}$ in terms of the behavior of their information complexity $n(ε,S_d)$ as a function of the accuracy $ε$ and the dimension $d$. By now a lot of effort was spend on either proving quantitative positive results (such as, e.g., the concrete dependence on $ε$ and $d$ within the well-established framework of polynomial tractability), or on qualitative negative results (which, e.g., state that a given problem suffers from the so-called curse of dimensionality). Although several weaker types of tractability were introduced recently, the theory of information-based complexity still lacks a notion which allows to quantify the exact (sub-/super-)exponential dependence of $n(ε,S_d)$ on both parameters $ε$ and $d$. In this paper we present the notion of $(s,t)$-weak tractability which attempts to fill this gap. Within this new framework the parameters $s$ and $t$ are used to quantitatively refine the huge class of polynomially intractable problems. For linear, compact operators between Hilbert spaces we provide characterizations of $(s,t)$-weak tractability w.r.t. the worst case setting in terms of singular values. In addition, our new notion is illustrated by classical examples which recently attracted some attention. In detail, we study approximation problems between periodic Sobolev spaces and integration problems for classes of smooth functions. Keywords: Information-based complexity, Multivariate numerical problems, Hilbert spaces, Tractablity, Approximation, Integration.

math.NA↗