Importance sampling schemes for evidence approximation in mixture models

The marginal likelihood is a central tool for drawing Bayesian inference about the number of components in mixture models. It is often approximated since the exact form is unavailable. A bias in the approximation may be due to an incomplete exploration by a simulated Markov chain (e.g., a Gibbs sequence) of the collection of posterior modes, a phenomenon also known as lack of label switching, as all possible label permutations must be simulated by a chain in order to converge and hence overcome the bias. In an importance sampling approach, imposing label switching to the importance function results in an exponential increase of the computational cost with the number of components. In this paper, two importance sampling schemes are proposed through choices for the importance function; a MLE proposal and a Rao-Blackwellised importance function. The second scheme is called dual importance sampling. We demonstrate that this dual importance sampling is a valid estimator of the evidence and moreover show that the statistical efficiency of estimates increases. To reduce the induced high demand in computation, the original importance function is approximated but a suitable approximation can produce an estimate with the same precision and with reduced computational workload.Comment: 24 pages, 5 figure

Security-voting structure and bidder screening

This paper analyzes how non-voting shares affect the takeover outcome in a single-bidder model with asymmetric information and private benefit extraction. In equilibrium, the target firm’s security-voting structure influences the bidder’s participation constraint and in response the shareholders’ conditional expectations about the post-takeover share value. Therefore, the structure can be chosen to discriminate among bidder types. Typically, the socially optimal structure deviates from one share - one vote to promote all and only value-increasing bids. As target shareholders ignore takeover costs, they prefer more takeovers and hence choose a smaller fraction of voting shares than is socially optimal. In either case, the optimal fraction of voting shares decreases with the quality of shareholder protection and increases with the incumbent manager’s ability. Finally, shareholder returns are higher when a given takeover probability is implemented by (more) non-voting shares rather than by (larger) private benefits

Dynamics of localized waves in 1D random potentials: statistical theory of the coherent forward scattering peak

As recently discovered [PRL ${\bf 109}$ 190601(2012)], Anderson localization in a bulk disordered system triggers the emergence of a coherent forward scattering (CFS) peak in momentum space, which twins the well-known coherent backscattering (CBS) peak observed in weak localization experiments. Going beyond the perturbative regime, we address here the long-time dynamics of the CFS peak in a 1D random system and we relate this novel interference effect to the statistical properties of the eigenfunctions and eigenspectrum of the corresponding random Hamiltonian. Our numerical results show that the dynamics of the CFS peak is governed by the logarithmic level repulsion between localized states, with a time scale that is, with good accuracy, twice the Heisenberg time. This is in perfect agreement with recent findings based on the nonlinear $\sigma$-model. In the stationary regime, the width of the CFS peak in momentum space is inversely proportional to the localization length, reflecting the exponential decay of the eigenfunctions in real space, while its height is exactly twice the background, reflecting the Poisson statistical properties of the eigenfunctions. Our results should be easily extended to higher dimensional systems and other symmetry classes.Comment: See the published article for the updated versio

Linked Data - the story so far

The term “Linked Data” refers to a set of best practices for publishing and connecting structured data on the Web. These best practices have been adopted by an increasing number of data providers over the last three years, leading to the creation of a global data space containing billions of assertions— the Web of Data. In this article, the authors present the concept and technical principles of Linked Data, and situate these within the broader context of related technological developments. They describe progress to date in publishing Linked Data on the Web, review applications that have been developed to exploit the Web of Data, and map out a research agenda for the Linked Data community as it moves forward

Momentum-space dynamics of Dirac quasiparticles in correlated random potentials: Interplay between dynamical and Berry phases

We consider Dirac quasi-particles, as realized with cold atoms loaded in a honeycomb lattice or in a $\pi$-flux square lattice, in the presence of a weak correlated disorder such that the disorder fluctuations do not couple the two Dirac points of the lattices. We numerically and theoretically investigate the time evolution of the momentum distribution of such quasi-particles when they are initially prepared in a quasi-monochromatic wave packet with a given mean momentum. The parallel transport of the pseudo-spin degree of freedom along scattering paths in momentum space generates a geometrical phase which alters the interference associated with reciprocal scattering paths. In the massless case, a well-known dip in the momentum distribution develops at backscattering (respective to the Dirac point considered) around the transport mean free time. This dip later vanishes in the honeycomb case because of trigonal warping. In the massive case, the dynamical phase of the scattering paths becomes crucial. Its interplay with the geometrical phase induces an additional transient broken reflection symmetry in the momentum distribution. The direction of this asymmetry is a property of the Dirac point considered, independent of the energy of the wave packet. These Berry phase effects could be observed in current cold atom lattice experiments.Comment: Additional data and explanations compared to version 1. See published article for the latest versio

Empowering Active Learning to Jointly Optimize System and User Demands

Existing approaches to active learning maximize the system performance by sampling unlabeled instances for annotation that yield the most efficient training. However, when active learning is integrated with an end-user application, this can lead to frustration for participating users, as they spend time labeling instances that they would not otherwise be interested in reading. In this paper, we propose a new active learning approach that jointly optimizes the seemingly counteracting objectives of the active learning system (training efficiently) and the user (receiving useful instances). We study our approach in an educational application, which particularly benefits from this technique as the system needs to rapidly learn to predict the appropriateness of an exercise to a particular user, while the users should receive only exercises that match their skills. We evaluate multiple learning strategies and user types with data from real users and find that our joint approach better satisfies both objectives when alternative methods lead to many unsuitable exercises for end users.Comment: To appear as a long paper in Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (ACL 2020). Download our code and simulated user models at github: https://github.com/UKPLab/acl2020-empowering-active-learnin

Collider Searches for Long-Lived Particles Beyond the Standard Model

Experimental tests of the Standard Model of particle physics (SM) find excellent agreement with its predictions. Since the original formation of the SM, experiments have provided little guidance regarding the explanations of phenomena outside the SM, such as the baryon asymmetry and dark matter. Nor have we understood the aesthetic and theoretical problems of the SM, despite years of searching for physics beyond the Standard Model (BSM) at particle colliders. Some BSM particles can be produced at colliders yet evade being discovered, if the reconstruction and analysis procedures not matched to characteristics of the particle. An example is particles with large lifetimes. As interest in searches for such long-lived particles (LLPs) grows rapidly, a review of the topic is presented in this article. The broad range of theoretical motivations for LLPs and the experimental strategies and methods employed to search for them are described. Results from decades of LLP searches are reviewed, as are opportunities for the next generation of searches at both existing and future experiments.Comment: 79 pages, 36 figures, submitted to Progress in Particle and Nuclear Physic