Nonuniversal transition to condensate formation in two-dimensional turbulence. (arXiv:1911.11315v1 [physics.flu-dyn])

The occurrence of system-scale coherent structures, so-called condensates, is a well-known phenomenon in two-dimensional turbulence. Here, the transition to condensate formation is investigated as a function of the magnitude of the force and for different types of forcing. Random forces with constant mean energy input lead to a supercritical transition, while forcing through a small-scale…

General time interval multidimensional BSDEs with generators satisfying a weak stochastic-monotonicity condition. (arXiv:1911.11179v1 [math.PR])

This paper establishes an existence and uniqueness result for the adapted solution of a general time interval multidimensional backward stochastic differential equation (BSDE), where the generator $g$ satisfies a weak stochastic-monotonicity condition and a general growth condition in the state variable $y$, and a stochastic-Lipschitz condition in the state variable $z$. This unifies and strengthens…

Configuration Spaces for the Working Undergraduate. (arXiv:1911.11186v1 [math.HO])

Configuration spaces form a rich class of topological objects which are not usually presented to an undergraduate audience. Our aim is to present configuration spaces in a manner accessible to the advanced undergraduate. We begin with a slight introduction to the topic before giving necessary background on algebraic topology. We then discuss configuration spaces of…

Reverse integral Hardy inequality on metric measure spaces. (arXiv:1911.11187v1 [math.AP])

In this note, we obtain a reverse version of the integral Hardy inequality on metric measure spaces. Moreover, we give necessary and sufficient conditions for the weighted reverse Hardy inequality to be true. The main tool in our proof is a continuous version of the reverse Minkowski inequality. Also, we present some consequences of the…

Inverse random source scattering for the Helmholtz equation with attenuation. (arXiv:1911.11189v1 [math.AP])

In this paper, a new model is proposed for the inverse random source scattering problem of the Helmholtz equation with attenuation. The source is assumed to be driven by a fractional Gaussian field whose covariance is represented by a classical pseudo-differential operator. The work contains three contributions. First, the connection is established between fractional Gaussian…

Playing it Safe: Adversarial Robustness with an Abstain Option. (arXiv:1911.11253v1 [cs.LG])

We explore adversarial robustness in the setting in which it is acceptable for a classifier to abstain—that is, output no class—on adversarial examples. Adversarial examples are small perturbations of normal inputs to a classifier that cause the classifier to give incorrect output; they present security and safety challenges for machine learning systems. In many safety-critical…

Cumulative Sum Ranking. (arXiv:1911.11255v1 [cs.LG])

The goal of Ordinal Regression is to find a rule that ranks items from a given set. Several learning algorithms to solve this prediction problem build an ensemble of binary classifiers. Ranking by Projecting uses interdependent binary perceptrons. These perceptrons share the same direction vector, but use different bias values. Similar approaches use independent direction…

Deep Reinforcement Learning for Multi-Driver Vehicle Dispatching and Repositioning Problem. (arXiv:1911.11260v1 [cs.LG])

Order dispatching and driver repositioning (also known as fleet management) in the face of spatially and temporally varying supply and demand are central to a ride-sharing platform marketplace. Hand-crafting heuristic solutions that account for the dynamics in these resource allocation problems is difficult, and may be better handled by an end-to-end machine learning method. Previous…

Host-based anomaly detection using Eigentraces feature extraction and one-class classification on system call trace data. (arXiv:1911.11284v1 [cs.LG])

This paper proposes a methodology for host-based anomaly detection using a semi-supervised algorithm namely one-class classifier combined with a PCA-based feature extraction technique called Eigentraces on system call trace data. The one-class classification is based on generating a set of artificial data using a reference distribution and combining the target class probability function with artificial…