Adaptive Seeding for Gaussian Mixture Models

We present new initialization methods for the expectation-maximization algorithm for multivariate Gaussian mixture models. Our methods are adaptions of the well-known $K$-means++ initialization and the Gonzalez algorithm. Thereby we aim to close the gap between simple random, e.g. uniform, and complex methods, that crucially depend on the right choice of hyperparameters. Our extensive experiments indicate the usefulness of our methods compared to common techniques and methods, which e.g. apply the original $K$-means++ and Gonzalez directly, with respect to artificial as well as real-world data sets.Comment: This is a preprint of a paper that has been accepted for publication in the Proceedings of the 20th Pacific Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2016. The final publication is available at link.springer.com (http://link.springer.com/chapter/10.1007/978-3-319-31750-2 24

Static and dynamic ionization levels of transition metal-doped zinc chalcogenides

Transition metal (TM) impurities in semiconductors have a considerable effect on the electronic properties and on the lattice vibrations. The unfilled d shell permits the impurity atoms to exist in a variety of charge states. In this work, the static donor and acceptor ionization energies of ZnX:M, with X = S, Se, Te and M:Sc, Ti, V, Fe, Co, Ni are obtained from first principles total energy calculations and compared with experimental results in the literature where they exist. From these results, many of the TM-doped zinc chalogenides have an amphoteric behavior. To analyze the rule of the deep gap levels in both the radiative and non-radiative processes, the dynamic ionization energies are obtained as a function of the inward and outward M–X displacements. In many cases, the changes in the mass and the force constants resulting from the substitution of an impurity center for a lattice atom are small. When the charge or the environment of the impurity changes, the electron population tend to remain compensated. As consequence, the changes in the lattice vibrational modes are small

Business angel exits: A theory of planned behaviour perspective

Although there are a handful of studies on business angel investment returns, the business angel literature has given little or no attention to exits and the exit strategy. This is surprising given that a primary objective of investing is to achieve a capital gain through some form of liquidity event. Using the theory of planned behaviour (TPB) as an interpretative heuristic, we examine how exits happen: specifically, what are the motivations to seek an exit and to what extent are they planned or opportunistic? Based on multiple case studies in which business angels were invited to tell the story of their most recent exit(s), the evidence suggests that the majority of liquidity events are the outcome of planned behaviour. We propose a typology of angel-backed investment exits as the basis for identifying future directions for research and developing practical advice to angels on effective business practices