Technical University of Berlin

About: Technical University of Berlin is a education organization based out in Berlin, Germany. It is known for research contribution in the topics: Laser & Catalysis. The organization has 27292 authors who have published 59342 publications receiving 1414623 citations. The organization is also known as: Technische Universität Berlin & TU Berlin.

Bayes point machines

Abstract: Kernel-classifiers comprise a powerful class of non-linear decision functions for binary classification. The support vector machine is an example of a learning algorithm for kernel classifiers that singles out the consistent classifier with the largest margin, i.e. minimal real-valued output on the training sample, within the set of consistent hypotheses, the so-called version space. We suggest the Bayes point machine as a well-founded improvement which approximates the Bayes-optimal decision by the centre of mass of version space. We present two algorithms to stochastically approximate the centre of mass of version space: a billiard sampling algorithm and a sampling algorithm based on the well known perceptron algorithm. It is shown how both algorithms can be extended to allow for soft-boundaries in order to admit training errors. Experimentally, we find that - for the zero training error case - Bayes point machines consistently outperform support vector machines on both surrogate data and real-world benchmark data sets. In the soft-boundary/soft-margin case, the improvement over support vector machines is shown to be reduced. Finally, we demonstrate that the real-valued output of single Bayes points on novel test points is a valid confidence measure and leads to a steady decrease in generalisation error when used as a rejection criterion.

Comprehensive Evaluation of CuBi2O4 as a Photocathode Material for Photoelectrochemical Water Splitting

Abstract: CuBi2O4 is a multinary p-type semiconductor that has recently been identified as a promising photocathode material for photoelectrochemical (PEC) water splitting. It has an optimal bandgap energy (∼1.8 eV) and an exceptionally positive photocurrent onset potential (>1 V vs RHE), making it an ideal candidate for the top absorber in a dual absorber PEC device. However, photocathodes made from CuBi2O4 have not yet demonstrated high photoconversion efficiencies, and the factors that limit the efficiency have not yet been fully identified. In this work we characterize CuBi2O4 photocathodes synthesized by a straightforward drop-casting procedure and for the first time report many of the quintessential material properties that are relevant to PEC water splitting. Our results provide important insights into the limitations of CuBi2O4 in regards to optical absorption, charge carrier transport, reaction kinetics, and stability. This information will be valuable in future work to optimize CuBi2O4 as a PEC material. ...

Autoregressive Moving Average Graph Filtering

Abstract: One of the cornerstones of the field of signal processing on graphs are graph filters, direct analogs of classical filters, but intended for signals defined on graphs. This paper brings forth new insights on the distributed graph filtering problem. We design a family of autoregressive moving average (ARMA) recursions, which are able to approximate any desired graph frequency response, and give exact solutions for specific graph signal denoising and interpolation problems. The philosophy to design the ARMA coefficients independently from the underlying graph renders the ARMA graph filters suitable in static and, particularly, time-varying settings. The latter occur when the graph signal and/or graph topology are changing over time. We show that in case of a time-varying graph signal, our approach extends naturally to a two-dimensional filter, operating concurrently in the graph and regular time domain. We also derive the graph filter behavior, as well as sufficient conditions for filter stability when the graph and signal are time varying. The analytical and numerical results presented in this paper illustrate that ARMA graph filters are practically appealing for static and time-varying settings, as predicted by theoretical derivations.