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Many standard optimization methods for segmentation and reconstruction compute ML model estimates for ap- pearance or geometry of segments, e.g. Zhu-Yuille [23], Torr [20], Chan-Vese [6], GrabCut [18], Delong et al. [8]. We observe that the standard likelihood term in these formu- lations corresponds to a generalized probabilistic K-means energy. In learning it is well known that this energy has a
Deep neural network architectures have recently produced excellent results in a variety of areas in artificial intelligence and visual recognition, well surpassing traditional shallow architectures trained using hand-designed features. The power of deep networks stems both from their ability to perform local computations followed by pointwise non-linearities over increasingly larger receptive fiel
We formulate two simple benchmark problems for event-based control, where the optimal solutions in the continuous-time setting turn out to be ordinary PI and PID controllers. The benchmarks can be used to compare the performance of continuous-time, discrete-time, and various event-based controllers with regard to for instance disturbance attenuation, control effort, and average sampling or actuati
In the day-to-day operation of a power system, the system operator repeatedly solves short-term generation planning problems. When formulating these problems the operators have to weigh the risk of costly failures against increased production costs. The resulting problems are often high-dimensional and various approximations have been suggested in the literature. In this article we formulate the
One of the most widely used strategies for visual object detection is based on exhaustive spatial hypothesis search. While methods like sliding windows have been successful and effective for many years, they are still brute-force, independent of the image content and the visual category being searched. In this paper we present principled sequential models that accumulate evidence collected at a sm
This paper presents a new black-box algorithm for identification of a nonlinear autonomous system in stable periodic motion. The particle filtering based algorithm models the signal as the output of a continuous-time second order ordinary differential equation (ODE). The model is selected based on previous work which proves that a second order ODE is sufficient to model a wide class of nonlinear s
In the framework of the subspace-based identification of linear systems, the first step for the construction of a state-space model from observed input-output data involves the estimation of the output predictor. Such construction is based on projection operations of certain structured data matrices onto suitable subspaces spanned by the collected data. To the purpose of predictive control using s
Applications hosted in the cloud have become indispensable in several contexts, with their performance often being key to business operation and their running costs needing to be minimized. To minimize running costs, most modern virtualization technologies such as Linux Containers, Xen, and KVM offer powerful resource control primitives for individual provisioning - that enable adding or removing
Controllers with a diagonal-plus-low-rank structure constitute a scalable class of controllers for multi-agent systems. Previous research has shown that diagonal-plus-low-rank control laws appear as the optimal solution to a class of multi-agent H2 coordination problems, which arise in the control of wind farms. In this paper we show that this result extends to the case where the information excha
Closed-loop positivity of feedback interconnections of positive monotone nonlinear systems is investigated. It is shown that an instantaneous gain condition on the open-loop systems which implies feedback well-posedness also guarantees feedback positivity. Furthermore, the notion of integral linear constraints (ILC) is utilised as a tool to characterise uncertainty in positive feedback systems. Ro
Quadratic optimization subject to linear constraints is a fundamental building-block in many other branches of applied mathematics. However, for large-scale systems, where a common global objective function is neither naturally defined nor easily computable, it is natural to view economic equilibrium theory as an alternative approach to design and analysis. Stability and robustness of equilibria c
Stable positive linear time-invariant autonomous systems admit diagonal quadratic Lyapunov functions. Such a property is known to be useful in distributed and scalable control of positive systems. In this paper, it is established that the same holds for exponentially stable positive discrete-time and continuous-time linear time-varying systems.
We consider a class of structured covariance completion problems which aim to complete partially known sample statistics in a way that is consistent with the underlying linear dynamics. The statistics of stochastic inputs are unknown and sought to explain the given correlations. Such inverse problems admit many solutions for the forcing correlations, but can be interpreted as an optimal low-rank a
Previous work on estimating the epipolar geometry of two views relies on being able to reliably match feature points based on appearance. In this paper, we go one step further and show that it is feasible to compute both the epipolar geometry and the correspondences at the same time based on geometry only. We do this in a globally optimal manner. Our approach is based on an efficient branch and bo
Future manufacturing systems need to be more flexible, to embrace tougher and constantly changing market demands. They also need to make better use of plant data, ideally utilizing all data from the entire plant. Low-level data should be refined to real-time information for decision making, to facilitate competitiveness through informed and timely decisions. The Line Information System Architectur
The Integral Quadratic Constraint (IQC) framework developed by Professor Yakubovich and his co-workers, see Yakubovich et.al. (2004), is one of few available constructive tools for establishing robust stability of nonlinear systems. An explicit format of stability conditions, procedures for computing a Lyapunov function and developed libraries IQCs for common nonlinearities in dynamics, all togeth
An extended Kalman-Yakubovich-Popov Lemma for positive systems is proved, which generalizes earlier versions in several respects: Non-strict inequalities are treated. Matrix assumptions are less restrictive. Moreover, a new equivalence is introduced in terms of linear programming rather than semi-definite programming. As a complement, we also prove that a symmetric Metzler matrix with rn non-zero
Future manufacturing systems need to be more flexible, to embrace tougher and constantly changing market demands. They need to make better use of plant data, ideally utilising all data from the entire plant. Low-level data should be refined toreal-time information for decision-making, to facilitate competitiveness through informed and timely decisions. The Line Information System Architecture (LIS
