A representer theorem for deep kernel learning

In this paper we provide a finite-sample and an infinite-sample representer theorem for the concatenation of (linear combinations of) kernel functions of reproducing kernel Hilbert spaces. These results serve as mathematical foundation for the analysis of machine learning algorithms based on compositions of functions. As a direct consequence in the finite-sample case, the corresponding infinite-dimensional minimization problems can be recast into (nonlinear) finite-dimensional minimization problems, which can be tackled with nonlinear optimization algorithms. Moreover, we show how concatenated machine learning problems can be reformulated as neural networks and how our representer theorem applies to a broad class of state-of-the-art deep learning methods

Analyzing I(2) Systems by Transformed Vector Autoregressions

We characterize the restrictions imposed by the minimal I(2)-to-I(1) transformation that underlies much applied work, e.g. on money demand relationships or open-economy pricing relationships. The relationship between the parameters of the original I(2) vector autoregression, including the coefficients of polynomially cointegrating relationships, and the transformed I(1) model is characterized. We discuss estimation of the transformed model subject to restrictions as well as the more commonly used approach of unrestricted reduced rank regression. Only a minor loss of efficiency is incurred by ignoring the restrictions in the empirical example and a simulation study. A properly transformed vector autoregression thus provides a practical and effective means for inference on the parameters of the I(2) model.cointegration; stochastic trend; price homogeneity; nominal; real; Monte Carlo experiment

The Economics of Yield-Driven Processes

The economic performance of many modern production processes is substantially influenced by process yields. Their first effect is on product cost — in some cases, low-yields can cause costs to double or worse. Yet measuring only costs can substantially underestimate the importance of yield improvement. We show that yields are especially important in periods of constrained capacity, such as new product ramp-up. Our analysis is illustrated with numerical examples taken from hard disk drive manufacturing. A three percentage point increase in yields can be worth about 6% of gross revenue and 17% of contribution. In fact, an eight percentage point improvement in process yields can outweigh a US$20/h increase in direct labor wages. Therefore, yields, in addition to or instead of labor costs, should be a focus of attention when making decisions such as new factory siting and type of automation. The paper also provides rules for when to rework, and shows that cost minimization logic can again give wrong answers

Embedding speech into virtual realities

In this work a speaker-independent speech recognition system is presented, which is suitable for implementation in Virtual Reality applications. The use of an artificial neural network in connection with a special compression of the acoustic input leads to a system, which is robust, fast, easy to use and needs no additional hardware, beside a common VR-equipment

Система контроля качества производства кабельных изделий

Разработана виртуальная панель, отображающая в реальном масштабе времени весь технологический процесс изготовления кабельных изделий. Предусмотрена возможность контроля любого конкретного параметра кабеля при помощи многооконного режима. В программном обеспечении применена нечеткая логика, позволяющая отслеживать нарушения производственного процесса и корректировать действия оператора

Parameter Optimisation of a Virtual Synchronous Machine in a Microgrid

Parameters of a virtual synchronous machine in a small microgrid are optimised. The dynamical behaviour of the system is simulated after a perturbation, where the system needs to return to its steady state. The cost functional evaluates the system behaviour for different parameters. This functional is minimised by Parallel Tempering. Two perturbation scenarios are investigated and the resulting optimal parameters agree with analytical predictions. Dependent on the focus of the optimisation different optima are obtained for each perturbation scenario. During the transient the system leaves the allowed voltage and frequency bands only for a short time if the perturbation is within a certain range.Comment: 17 pages, 5 figure