Learning Visual Attributes

We present a probabilistic generative model of visual attributes, together with an efficient learning algorithm. Attributes are visual qualities of objects, such as ‘red’, ‘striped’, or ‘spotted’. The model sees attributes as patterns of image segments, repeatedly sharing some characteristic properties. These can be any combination of appearance, shape, or the layout of segments within the pattern. Moreover, attributes with general appearance are taken into account, such as the pattern of alternation of any two colors which is characteristic for stripes. To enable learning from unsegmented training images, the model is learnt discriminatively, by optimizing a likelihood ratio. As demonstrated in the experimental evaluation, our model can learn in a weakly supervised setting and encompasses a broad range of attributes. We show that attributes can be learnt starting from a text query to Google image search, and can then be used to recognize the attribute and determine its spatial extent in novel real-world images.

A Conditional Random Field for Multiple-Instance Learning

We present MI-CRF, a conditional random field (CRF) model for multiple instance learning (MIL). MI-CRF models bags as nodes in a CRF with instances as their states. It combines discriminative unary instance classifiers and pairwise dissimilarity measures. We show that both forces improve the classification performance. Unlike other approaches, MI-CRF considers all bags jointly during training as well as during testing. This makes it possible to classify test bags in an imputation setup. The parameters of MI-CRF are learned using constraint generation. Furthermore, we show that MI-CRF can incorporate previous MIL algorithms to improve on their results. MI-CRF obtains competitive results on five standard MIL datasets. 1

Escape of mass in zero-range processes with random rates

We consider zero-range processes in ${\mathbb{Z}}^d$ with site dependent jump rates. The rate for a particle jump from site $x$ to $y$ in ${\mathbb{Z}}^d$ is given by $\lambda_xg(k)p(y-x)$, where $p(\cdot)$ is a probability in ${\mathbb{Z}}^d$, $g(k)$ is a bounded nondecreasing function of the number $k$ of particles in $x$ and $\lambda =\{\lambda_x\}$ is a collection of i.i.d. random variables with values in $(c,1]$, for some $c>0$. For almost every realization of the environment $\lambda$ the zero-range process has product invariant measures $\{{\nu_{\lambda, v}}:0\le v\le c\}$ parametrized by $v$, the average total jump rate from any given site. The density of a measure, defined by the asymptotic average number of particles per site, is an increasing function of $v$. There exists a product invariant measure ${\nu _{\lambda, c}}$, with maximal density. Let $\mu$ be a probability measure concentrating mass on configurations whose number of particles at site $x$ grows less than exponentially with $\|x\|$. Denoting by $S_{\lambda}(t)$ the semigroup of the process, we prove that all weak limits of $\{\mu S_{\lambda}(t),t\ge 0\}$ as $t\to \infty$ are dominated, in the natural partial order, by ${\nu_{\lambda, c}}$. In particular, if $\mu$ dominates ${\nu _{\lambda, c}}$, then $\mu S_{\lambda}(t)$ converges to ${\nu_{\lambda, c}}$. The result is particularly striking when the maximal density is finite and the initial measure has a density above the maximal.Comment: Published at http://dx.doi.org/10.1214/074921707000000300 in the IMS Lecture Notes Monograph Series (http://www.imstat.org/publications/lecnotes.htm) by the Institute of Mathematical Statistics (http://www.imstat.org

Gravitational waves from neutron stars described by modern EOS

The frequencies and damping times of neutron star (and quark star) oscillations have been computed using the most recent equations of state available in the literature. We find that some of the empirical relations that connect the frequencies and damping times of the modes to the mass and radius of the star, and that were previously derived in the literature need to be modified.Comment: 3 pages, 1+1 figures, to appear in the Proceedings of "XVI SIGRAV Conference", Vietri sul Mare (Italy), 13-16 September 200

A new approach to the study of quasi-normal modes of rotating stars

We propose a new method to study the quasi-normal modes of rotating relativistic stars. Oscillations are treated as perturbations in the frequency domain of the stationary, axisymmetric background describing a rotating star. The perturbed quantities are expanded in circular harmonics, and the resulting 2D-equations they satisfy are integrated using spectral methods in the (r,theta)-plane. The asymptotic conditions at infinity, needed to find the mode frequencies, are implemented by generalizing the standing wave boundary condition commonly used in the non rotating case. As a test, the method is applied to find the quasi-normal mode frequencies of a slowly rotating star.Comment: 24 pages, 7 figures, submitted to Phys. Rev.

The imprint of the equation of state on the axial w-modes of oscillating neutron stars

We discuss the dependence of the pulsation frequencies of the axial quasi-normal modes of a nonrotating neutron star upon the equation of state describing the star interior. The continued fraction method has been used to compute the complex frequencies for a set of equations of state based on different physical assumptions and spanning a wide range of stiffness. The numerical results show that the detection of axial gravitational waves would allow to discriminate between the models underlying the different equation of states, thus providing relevant information on both the structure of neutron star matter and the nature of the hadronic interactions.Comment: 9 pages, 7 figures, mn.st

Unstable g-modes in Proto-Neutron Stars

In this article we study the possibility that, due to non-linear couplings, unstable g-modes associated to convective motions excite stable oscillating g-modes. This problem is of particular interest, since gravitational waves emitted by a newly born proto-neutron star pulsating in its stable g-modes would be in the bandwidth of VIRGO and LIGO. Our results indicate that nonlinear saturation of unstable modes occurs at relatively low amplitudes, and therefore, even if there exists a coupling between stable and unstable modes, it does not seem to be sufficiently effective to explain, alone, the excitation of the oscillating g-modes found in hydrodynamical simulations.Comment: 10 pages, 3 figures, to appear on Class. Quant. Gra