Agency: European Commission | Branch: H2020 | Program: RIA | Phase: INT-10-2015 | Award Amount: 2.49M | Year: 2016
Southeast Europe has seen a century of continuous transformation and transition the disappearance and emergence of states, political and legal systems, ideologies, institutions, and social classes. This has been accompanied by a stability of social practices resistant to change. Shaken by radically changing ideological and legal structures, citizens rely on customary and informal social networks of kin, symbolic kin, and friends for meeting economic needs, and on clan- or kin-related structures rather than the rule of law for security and protection. We trace the persistence of informal practices to: 1) the external origin of major transformations, including the transitions to and from socialism; 2) the incomplete character of change, which has tended to be replaced by equally radical but diametrically opposed projects; 3) the development of a buffer culture based on informal practices, directed to enabling people to survive under unstable conditions; and 4) the widening gap between formal institutions and informal social practices. The distance between proclaimed goals and existing practices represents the key challenge to the European integration of Balkan societies. The integration process could end with superficial change, behind which the real social life of corruption, clientelism, tension, inequality, and exclusion will continue to unfold. We propose to explicate the key formal and informal rules of the game, and to identify and decipher the unwritten rules which underpin tactical maneuvering between formal and informal institutions, in various spheres and at various levels of social life. These would then be compared to the demands and recommendations laid out in the key EU documents outlining expectations from Southeast European states. The goal is to contribute to the formulation of policy recommendations which would aim not to eradicate informal practices, but to close the gap between formal and informal institutions in Balkan societies.
Cherian A.,University of Minnesota |
Sra S.,Empirical |
Banerjee A.,University of Minnesota |
Papanikolopoulos N.,University of Minnesota
IEEE Transactions on Pattern Analysis and Machine Intelligence | Year: 2013
Covariance matrices have found success in several computer vision applications, including activity recognition, visual surveillance, and diffusion tensor imaging. This is because they provide an easy platform for fusing multiple features compactly. An important task in all of these applications is to compare two covariance matrices using a (dis)similarity function, for which the common choice is the Riemannian metric on the manifold inhabited by these matrices. As this Riemannian manifold is not flat, the dissimilarities should take into account the curvature of the manifold. As a result, such distance computations tend to slow down, especially when the matrix dimensions are large or gradients are required. Further, suitability of the metric to enable efficient nearest neighbor retrieval is an important requirement in the contemporary times of big data analytics. To alleviate these difficulties, this paper proposes a novel dissimilarity measure for covariances, the Jensen-Bregman LogDet Divergence (JBLD). This divergence enjoys several desirable theoretical properties and at the same time is computationally less demanding (compared to standard measures). Utilizing the fact that the square root of JBLD is a metric, we address the problem of efficient nearest neighbor retrieval on large covariance datasets via a metric tree data structure. To this end, we propose a K-Means clustering algorithm on JBLD. We demonstrate the superior performance of JBLD on covariance datasets from several computer vision applications. © 1979-2012 IEEE.
Grosse-Wentrup M.,Empirical |
Journal of Neural Engineering | Year: 2012
Subjects operating a brain-computer interface (BCI) based on sensorimotor rhythms exhibit large variations in performance over the course of an experimental session. Here, we show that high-frequency γ-oscillations, originating in fronto-parietal networks, predict such variations on a trial-to-trial basis. We interpret this finding as empirical support for an influence of attentional networks on BCI performance via modulation of the sensorimotor rhythm. © 2012 IOP Publishing Ltd.
Johnstone N.,Empirical |
Hascic I.,Empirical |
Popp D.,Syracuse University
Environmental and Resource Economics | Year: 2010
This paper examines the effect of environmental policies on technological innovation in the specific case of renewable energy. The analysis is conducted using patent data on a panel of 25 countries over the period 1978-2003. We find that public policy plays a significant role in determining patent applications. Different types of policy instruments are effective for different renewable energy sources. Broad-based policies, such as tradable energy certificates, are more likely to induce innovation on technologies that are close to competitive with fossil fuels. More targeted subsidies, such as feed-in tariffs, are needed to induce innovation on more costly energy technologies, such as solar power. Springer Science+Business Media B.V. 2009.
Hennig P.,Empirical |
Journal of Machine Learning Research | Year: 2013
Four decades after their invention, quasi-Newton methods are still state of the art in unconstrained numerical optimization. Although not usually interpreted thus, these are learning algorithms that fit a local quadratic approximation to the objective function. We show that many, including the most popular, quasi-Newton methods can be interpreted as approximations of Bayesian linear regression under varying prior assumptions. This new notion elucidates some shortcomings of classical algorithms, and lights the way to a novel nonparametric quasi-Newton method, which is able to make more efficient use of available information at computational cost similar to its predecessors. © 2013 Philipp Hennig and Martin Kiefel.
Hennig P.,Empirical |
Journal of Machine Learning Research | Year: 2012
Contemporary global optimization algorithms are based on local measures of utility, rather than a probability measure over location and value of the optimum. They thus attempt to collect low function values, not to learn about the optimum. The reason for the absence of probabilistic global optimizers is that the corresponding inference problem is intractable in several ways. This paper develops desiderata for probabilistic optimization algorithms, then presents a concrete algorithm which addresses each of the computational intractabilities with a sequence of approximations and explicitly addresses the decision problem of maximizing information gain from each evaluation. © 2012 Philipp Hennig and Christian J. Schuler.
Empirical | Date: 2016-02-25
A spinal implant for limiting flexion of the spine includes a tether structure for encircling adjacent spinal processes. Usually, a pair of compliance members will be provided as part of the tether structure for elastically limiting flexion while permitting an extension. A cross-member is provided between the compliance member or other portions of the tether structure to stabilize the tether structure and prevent misalignment after implantation.
Empirical | Date: 2015-12-28
The present invention provides systems and methods for deploying implantable devices within the body. The delivery and deployment systems include at least one catheter or an assembly of catheters for selectively positioning the lumens of the implant to within target vessels. Various deployment and attachment mechanisms are provided for selectively deploying the implants.
Empirical | Date: 2016-09-28
A system for restricting flexion of a spinal segment in a patient comprises a constraint device having a tether structure and a compliance member coupled with the tether structure. The tether structure is adapted to be coupled with a superior spinous process and a sacrum. The system also includes an anchor member that is anchored to the sacrum. The anchor member has an attachment feature that is adapted to couple with the constraint device.
Empirical | Date: 2016-02-25
A spinal treatment system includes a constraint device having an upper tether portion, a lower tether portion and a compliance member coupled therebetween. The upper tether portion is coupled with a superior spinous process of a spinal segment in a patient and the lower tether portion is coupled with an inferior spinous process or sacrum of the spinal segment. The length or tension in the constraint device is adjustable so that the construct of the tether portions and the compliance member provides a force resistant to flexion of the spinal segment. The system also includes a first prosthesis coupled with the spinal segment, wherein the constraint device modulates loads borne by the prosthesis or by tissue adjacent thereto.