The city as a construction site — a visual record of a multisensory experience

In this article, I consider the reception of images that are present in a city space. I focus on the juxtaposition of computer‑generated images covering fences surrounding construction sites and the real spaces which they screen from view. I postulate that a visual experience is dependent on input from the other human senses. While looking at objects, we are not only standing in front of them but are being influenced by them. Seeing does not leave a physical trace on the object; instead the interference is more subtle — it influences the way in which we perceive space. Following in the footsteps of Sarah Pink, Michael Taussig and William J. T. Mitchell, I show that seeing (to paraphrase the title of an article by the last of the above mentioned scholars) is a cultural practice. The last part of the article presents a visual essay as a method that can contribute to cultural urban studies. I give as an example of such a method a photo‑essay about chosen construction sites in Poznań, which I photographed between December 2014 and June 2015

Human~Divine Communication as a Paradigm for Power: al-Tha'labi's Presentation of Q. 38:24 and Q. 38:34

Verse 24 to 25 of sura 38 (Sad) of the Qur'an tell us 'David realized that We had been testing him, so he asked forgiveness of his Lord, fell down on his knees, and repented: We forgave him [his misdeed]. His reward will be nearness to Us, a good place to return to'; verse 34 to 35 of the same sura tell us 'We certainly tested Solomon, reducing him to a mere skeleton on the throne. He turned to Us and prayed: 'Lord, forgive me! Grant me such power as no one after me will have -- You are the Most Generous Provider', then, at verse 40, 'His reward will be nearness to Us, a good place to return to'. Yet the medieval Muslim historiographical tradition presents very different narratives, and very different personalities, in elucidation of these two episodes. The two questions that will be addressed in this essay are: restricting our focus to communication patterns and how God is presented in the narrative, how do these two narratives differ? And, secondly, can we find reasons in the text of the Qur'anic passages themselves for why they differ

Frequentist optimality of Bayesian wavelet shrinkage rules for Gaussian and non-Gaussian noise

The present paper investigates theoretical performance of various Bayesian wavelet shrinkage rules in a nonparametric regression model with i.i.d. errors which are not necessarily normally distributed. The main purpose is comparison of various Bayesian models in terms of their frequentist asymptotic optimality in Sobolev and Besov spaces. We establish a relationship between hyperparameters, verify that the majority of Bayesian models studied so far achieve theoretical optimality, state which Bayesian models cannot achieve optimal convergence rate and explain why it happens.Comment: Published at http://dx.doi.org/10.1214/009053606000000128 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Solution of linear ill-posed problems using overcomplete dictionaries

In the present paper we consider application of overcomplete dictionaries to solution of general ill-posed linear inverse problems. Construction of an adaptive optimal solution for such problems usually relies either on a singular value decomposition or representation of the solution via an orthonormal basis. The shortcoming of both approaches lies in the fact that, in many situations, neither the eigenbasis of the linear operator nor a standard orthonormal basis constitutes an appropriate collection of functions for sparse representation of the unknown function. In the context of regression problems, there have been an enormous amount of effort to recover an unknown function using an overcomplete dictionary. One of the most popular methods, Lasso, is based on minimizing the empirical likelihood and requires stringent assumptions on the dictionary, the, so called, compatibility conditions. While these conditions may be satisfied for the original dictionary functions, they usually do not hold for their images due to contraction imposed by the linear operator. In what follows, we bypass this difficulty by a novel approach which is based on inverting each of the dictionary functions and matching the resulting expansion to the true function, thus, avoiding unrealistic assumptions on the dictionary and using Lasso in a predictive setting. We examine both the white noise and the observational model formulations and also discuss how exact inverse images of the dictionary functions can be replaced by their approximate counterparts. Furthermore, we show how the suggested methodology can be extended to the problem of estimation of a mixing density in a continuous mixture. For all the situations listed above, we provide the oracle inequalities for the risk in a finite sample setting. Simulation studies confirm good computational properties of the Lasso-based technique