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- Brownian motion with discontinuous drift (1)
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We consider the Navier-Stokes equations in the layer R^n x [0,T] over R^n with finite T > 0. Using the standard fundamental solutions of the Laplace operator and the heat operator, we reduce the Navier-Stokes equations to a nonlinear Fredholm equation of the form (I+K) u = f, where K is a compact continuous operator in anisotropic normed Hölder spaces weighted at the point at infinity with respect to the space variables. Actually, the weight function is included to provide a finite energy estimate for solutions to the Navier-Stokes equations for all t in [0,T]. On using the particular properties of the de Rham complex we conclude that the Fréchet derivative (I+K)' is continuously invertible at each point of the Banach space under consideration and the map I+K is open and injective in the space. In this way the Navier-Stokes equations prove to induce an open one-to-one mapping in the scale of Hölder spaces.

Convoluted Brownian motion
(2016)

In this paper we analyse semimartingale properties of a class of Gaussian periodic processes, called convoluted Brownian motions, obtained by convolution between a deterministic function and a Brownian motion. A classical
example in this class is the periodic Ornstein-Uhlenbeck process. We compute their characteristics and show that in general, they are neither
Markovian nor satisfy a time-Markov field property. Nevertheless, by enlargement
of filtration and/or addition of a one-dimensional component, one can in some case recover the Markovianity. We treat exhaustively the case of the bidimensional trigonometric convoluted Brownian motion and the higher-dimensional monomial convoluted Brownian motion.

In order to evade detection by network-traffic analysis, a growing proportion of malware uses the encrypted HTTPS protocol. We explore the problem of detecting malware on client computers based on HTTPS traffic analysis. In this setting, malware has to be detected based on the host IP address, ports, timestamp, and data volume information of TCP/IP packets that are sent and received by all the applications on the client. We develop a scalable protocol that allows us to collect network flows of known malicious and benign applications as training data and derive a malware-detection method based on a neural networks and sequence classification. We study the method's ability to detect known and new, unknown malware in a large-scale empirical study.

When trying to extend the Hodge theory for elliptic complexes on compact closed manifolds to the case of compact manifolds with boundary one is led to a boundary value problem for
the Laplacian of the complex which is usually referred to as Neumann problem. We study the Neumann problem for a larger class of sequences of differential operators on
a compact manifold with boundary. These are sequences of small curvature, i.e., bearing the property that the composition of any two neighbouring operators has order less than two.

This article assesses the distance between the laws of stochastic differential equations with multiplicative Lévy noise on path space in terms of their characteristics. The notion of transportation distance on the set of Lévy kernels introduced by Kosenkova and Kulik yields a natural and statistically tractable upper bound on the noise sensitivity. This extends recent results for the additive case in terms of coupling distances to the multiplicative case. The strength of this notion is shown in a statistical implementation for simulations and the example of a benchmark time series in paleoclimate.

The aim of this paper is to bring together two areas which are of great importance for the study of overdetermined boundary value problems. The first area is homological algebra which is the main tool in constructing the formal theory of overdetermined problems. And the second area is the global calculus of pseudodifferential operators which allows one to develop explicit analysis.

Postcolonial Justice
(2016)

Kleine Kosmopolitismen
(2016)

Luhmann in da Contact Zone
(2016)

Our aim in this contribution is to productively engage with the abstractions and complexities of Luhmann’s conceptions of society from a postcolonial perspective, with a particular focus on the explanatory powers of his sociological systems theory when it leaves the realms of Europe and ventures to describe regions of the global South. In view of its more recent global reception beyond Europe, our aim is to thus – following the lead of Dipesh Chakrabarty – provincialize Luhmann’s system theory especially with regard to its underlying assumptions about a global “world society”. For these purposes, we intend to revisit Luhmann in the post/colonial contact zone: We wish to reread Luhmann in the context of spaces of transcultural encounter where “global designs and local histories” (Mignolo), where inclusion into and exclusion from “world society” (Luhmann) clash and interact in intricate ways. The title of our contribution, ‘Luhmann in da Contact Zone’ is deliberately ambiguous: On the one hand, we of course use ‘Luhmann’ metonymically, as representative of a highly complex theoretical design. We shall cursorily outline this design with a special focus on the notion of a singular, modern “world society”, only to confront it with the epistemic challenges of the contact zone. On the other hand, this critique will also involve the close observation of Niklas Luhman as a human observer (a category which within the logic of systems theory actually does not exist) who increasingly transpires in his late writings on exclusion in the global South. By following this dual strategy, we wish to trace an increasing fracture between one Luhmann and the other, between abstract theoretical design and personalized testimony. It is by exploring and measuring this fracture that we hope to eventually be able to map out the potential of a possibly more productive encounter between systems theory and specific strands of postcolonial theory for a pluritopic reading of global modernity.

Reflections of Lusáni Cissé
(2016)

Recollecting Bones
(2016)

In the same “guarded, roundabout and reticent way” which Lindsay Barrett invokes for Australian conversations about imperial injustice, Germans, too, must begin to more systematically explore, in Paul Gilroy’s words, “the connections and the differences between anti-semitism and anti-black and other racisms and asses[s] the issues that arise when it can no longer be denied that they interacted over a long time in what might be seen as Fascism’s intellectual, ethical and scientific pre-history” (Gilroy 1996: 26). In the meantime, we need to care for the dead. We need to return them, first, from the status of scientific objects to the status of ancestral human beings, and then progressively, and proactively, as close as possible to the care of those communities from whom they were stolen.

Postcolonial Piracy
(2016)

Media piracy is a contested term in the academic as much as the public debate. It is used by the corporate industries as a synonym for the theft of protected media content with disastrous economic consequences. It is celebrated by technophile elites as an expression of freedom that ensures creativity as much as free market competition. Marxist critics and activists promote flapiracy as a subversive practice that undermines the capitalist world system and its structural injustices. Artists and entrepreneurs across the globe curse it as a threat to their existence, while many use pirate infrastructures and networks fundamentally for the production and dissemination of their art. For large sections of the population across the global South, piracy is simply the only means of accessing the medial flows of a progressively globalising planet.

Using an algorithm based on a retrospective rejection sampling scheme, we propose an exact simulation of a Brownian diffusion whose drift admits several jumps. We treat explicitly and extensively the case of two jumps, providing numerical simulations. Our main contribution is to manage the technical difficulty due to the presence of two jumps thanks to a new explicit expression of the transition density of the skew Brownian motion with two semipermeable barriers and a constant drift.

We consider a statistical inverse learning problem, where we observe the image of a function f through a linear operator A at i.i.d. random design points X_i, superposed with an additional noise. The distribution of the design points is unknown and can be very general. We analyze simultaneously the direct (estimation of Af) and the inverse (estimation of f) learning problems. In this general framework, we obtain strong and weak minimax optimal rates of convergence (as the number of observations n grows large) for a large class of spectral regularization methods over regularity classes defined through appropriate source conditions. This improves on or completes previous results obtained in related settings. The optimality of the obtained rates is shown not only in the exponent in n but also in the explicit dependence of the constant factor in the variance of the noise and the radius of the source condition set.

We prove statistical rates of convergence for kernel-based least squares regression from i.i.d. data using a conjugate gradient algorithm, where regularization against overfitting is obtained by early stopping. This method is related to Kernel Partial Least Squares, a regression method that combines supervised dimensionality reduction with least squares projection. Following the setting introduced in earlier related literature, we study so-called "fast convergence rates" depending on the regularity of the target regression function (measured by a source condition in terms of the kernel integral operator) and on the effective dimensionality of the data mapped into the kernel space. We obtain upper bounds, essentially matching known minimax lower bounds, for the L^2 (prediction) norm as well as for the stronger Hilbert norm, if the true
regression function belongs to the reproducing kernel Hilbert space. If the latter assumption is not fulfilled, we obtain similar convergence rates for appropriate norms, provided additional unlabeled data are available.

We elaborate a boundary Fourier method for studying an analogue of the Hilbert problem for analytic functions within the framework of generalised Cauchy-Riemann equations. The boundary value problem need not satisfy the Shapiro-Lopatinskij condition and so it fails to be Fredholm in Sobolev spaces. We show a solvability condition of the Hilbert problem, which looks like those for ill-posed
problems, and construct an explicit formula for approximate solutions.