arXiv subjects

Xiao Wang

Publications and source records attributed to Xiao Wang.

747 records · Page 42Linked to original sources

arXiv2011

Uncovering Social Network Sybils in the Wild

Sybil accounts are fake identities created to unfairly increase the power or resources of a single malicious user. Researchers have long known about the existence of Sybil accounts in online communities such as file-sharing systems, but have not been able to perform large scale measurements to detect them or measure their activities. In this paper, we describe our efforts to detect, characterize and understand Sybil account activity in the Renren online social network (OSN). We use ground truth provided by Renren Inc. to build measurement based Sybil account detectors, and deploy them on Renren to detect over 100,000 Sybil accounts. We study these Sybil accounts, as well as an additional 560,000 Sybil accounts caught by Renren, and analyze their link creation behavior. Most interestingly, we find that contrary to prior conjecture, Sybil accounts in OSNs do not form tight-knit communities. Instead, they integrate into the social graph just like normal users. Using link creation timestamps, we verify that the large majority of links between Sybil accounts are created accidentally, unbeknownst to the attacker. Overall, only a very small portion of Sybil accounts are connected to other Sybils with social links. Our study shows that existing Sybil defenses are unlikely to succeed in today's OSNs, and we must design new techniques to effectively detect and defend against Sybil attacks.

cs.SI↗

arXiv2011

Semiparametric Additive Transformation Model under Current Status Data

We consider the efficient estimation of the semiparametric additive transformation model with current status data. A wide range of survival models and econometric models can be incorporated into this general transformation framework. We apply the B-spline approach to simultaneously estimate the linear regression vector, the nondecreasing transformation function, and a set of nonparametric regression functions. We show that the parametric estimate is semiparametric efficient in the presence of multiple nonparametric nuisance functions. An explicit consistent B-spline estimate of the asymptotic variance is also provided. All nonparametric estimates are smooth, and shown to be uniformly consistent and have faster than cubic rate of convergence. Interestingly, we observe the convergence rate interfere phenomenon, i.e., the convergence rates of B-spline estimators are all slowed down to equal the slowest one. The constrained optimization is not required in our implementation. Numerical results are used to illustrate the finite sample performance of the proposed estimators.

math.ST↗

arXiv2009

Local Asymptotics of P-Spline Smoothing

This paper addresses asymptotic properties of general penalized spline estimators with an arbitrary B-spline degree and an arbitrary order difference penalty. The estimator is approximated by a solution of a linear differential equation subject to suitable boundary conditions. It is shown that, in certain sense, the penalized smoothing corresponds approximately to smoothing by the kernel method. The equivalent kernels for both inner points and boundary points are obtained with the help of Green's functions of the differential equation. Further, the asymptotic normality is established for the estimator at interior points. It is shown that the convergence rate is independent of the degree of the splines, and the number of knots does not affect the asymptotic distribution, provided that it tends to infinity fast enough.

math.ST↗

arXiv2008

Cosmological Constraints from Hubble parameter $H(z)$ and SN Ia observations

In this paper, we use a set of observational $H(z)$ data (OHD) to constrain the $Λ$CDM cosmology. This data set can be derived from the differential ages of the passively evolving galaxies. Meanwhile, the $\mathcal {A}$-parameter, which describes the Baryonic Acoustic Oscillation (BAO) peak, and the newly measured value of the Cosmic Microwave Background (CMB) shift parameter $\mathcal {R}$ are used to present combinational constraints on the same cosmology. The combinational constraints favor an accelerating flat universe while the flat $Λ$CDM cosmology is also analyzed in the same way. We obtain a result compatible with that by many other independent cosmological observations. We find that the observational $H(z)$ data set is a complementarity to other cosmological probes.

astro-ph↗

arXiv2007

A Kiefer--Wolfowitz comparison theorem for Wicksell's problem

We extend the isotonic analysis for Wicksell's problem to estimate a regression function, which is motivated by the problem of estimating dark matter distribution in astronomy. The main result is a version of the Kiefer--Wolfowitz theorem comparing the empirical distribution to its least concave majorant, but with a convergence rate $n^{-1}\log n$ faster than $n^{-2/3}\log n$. The main result is useful in obtaining asymptotic distributions for estimators, such as isotonic and smooth estimators.

math.ST↗

arXiv2007

Velocity Dispersion Profiles of Seven Dwarf Spheroidal Galaxies

We present stellar velocity dispersion profiles for seven Milky Way dwarf spheroidal (dSph) satellite galaxies. We have measured 8394 line-of-sight velocities (+/- 2.5 km/s) for 6804 stars from high-resolution spectra obtained at the Magellan and MMT telescopes. We combine these new data with previously published velocities to obtain the largest available kinematic samples, which include more than 5500 dSph members. All the measured dSphs have stellar velocity dispersion of order 10 km/s that remains approximately constant with distance from the dSph center, out to and in some cases beyond the radius at which the mean surface brightness falls to the background level. Assuming dSphs reside within dark matter halos characterized by the NFW density profile, we obtain reasonable fits to the empirical velocity dispersion profiles. These fits imply that, among the seven dSphs, M_vir ~ 10^[8-9] M_sun. The mass enclosed at a radius of 600 pc, the region common to all data sets, ranges from (2-7) x 10^7 M_sun .

astro-ph↗

arXiv2006

Variable-free exploration of stochastic models: a gene regulatory network example

Finding coarse-grained, low-dimensional descriptions is an important task in the analysis of complex, stochastic models of gene regulatory networks. This task involves (a) identifying observables that best describe the state of these complex systems and (b) characterizing the dynamics of the observables. In a previous paper [13], we assumed that good observables were known a priori, and presented an equation-free approach to approximate coarse-grained quantities (i.e, effective drift and diffusion coefficients) that characterize the long-time behavior of the observables. Here we use diffusion maps [9] to extract appropriate observables ("reduction coordinates") in an automated fashion; these involve the leading eigenvectors of a weighted Laplacian on a graph constructed from network simulation data. We present lifting and restriction procedures for translating between physical variables and these data-based observables. These procedures allow us to perform equation-free coarse-grained, computations characterizing the long-term dynamics through the design and processing of short bursts of stochastic simulation initialized at appropriate values of the data-based observables.

q-bio.QM↗

arXiv2006

Internal Kinematics of the Fornax Dwarf Spheroidal Galaxy

We present new radial velocity results for 176 stars in the Fornax dwarf spheroidal galaxy, of which at least 156 are probable Fornax members. We combine with previously published data to obtain a radial velocity sample with 206 stars, of which at least 176 are probable Fornax members. We detect the hint of rotation about an axis near Fornax's morphological minor axis, though the significance of the rotation signal in the galactic rest frame is sensitive to the adopted value of Fornax's proper motion. Regardless, the observed stellar kinematics are dominated by random motions, and we do not find kinematic evidence of tidal disruption. The projected velocity dispersion profile of the binned dataset remains flat over the sampled region, which reaches a maximum angular radius of 65 arcmin. Single-component King models in which mass follows light fail to reproduce the observed flatness of the velocity dispersion profile. Two-component (luminous plus dark matter) models can reproduce the data, provided the dark component extends sufficiently beyond the luminous component, and the central dark matter density is of the same order as the central luminous density. These requirements suggest a more massive, darker Fornax than standard core-fitting analyses have previously concluded, with M/L_V over the sampled region reaching 10 to 40 times the M/L_V of the luminous component. We also apply a non-parametric mass estimation technique, introduced in a companion paper. Though it is designed to operate on datasets containing velocities for $>$1000 stars, the estimation yields preliminary results suggesting M/L_V ~ 15 inside r < 1.5 kpc.

astro-ph↗

arXiv2005

Estimating Dark Matter Distributions

Thanks to instrumental advances, new, very large kinematic datasets for nearby dwarf spheroidal (dSph) galaxies are on the horizon. A key aim of these datasets is to help determine the distribution of dark matter in these galaxies. Past analyses have generally relied on specific dynamical models or highly restrictive dynamical assumptions. We describe a new, non-parametric analysis of the kinematics of nearby dSph galaxies designed to take full advantage of the future large datasets. The method takes as input the projected positions and radial velocities of stars known to be members of the galaxies, but does not use any parametric dynamical model, nor the assumption that the mass distribution follows that of the visible matter. The problem of estimating the radial mass distribution, M(r) (the mass interior to true radius r), is converted into a problem of estimating a regression function non-parametrically. From the Jeans Equation we show that the unknown regression function is subject to fundamental shape restrictions which we exploit in our analysis using statistical techniques borrowed from isotonic estimation and spline smoothing. Simulations indicate that M(r) can be estimated to within a factor of two or better with samples as small as 1000 stars over almost the entire radial range sampled by the kinematic data. The technique is applied to a sample of 181 stars in the Fornax dSph galaxy. We show that the galaxy contains a significant, extended dark halo some ten times more massive than its baryonic component. Though applied here to dSph kinematics, this approach can be used in the analysis of any kinematically hot stellar system in which the radial velocity field is discretely sampled.

astro-ph↗