arXiv subjects

Ke Wang

Publications and source records attributed to Ke Wang.

710 records · Page 40Linked to original sources

arXiv2011

Random covariance matrices: Universality of local statistics of eigenvalues up to the edge

We study the universality of the eigenvalue statistics of the covariance matrices $\frac{1}{n}M^* M$ where $M$ is a large $p\times n$ matrix obeying condition $\bf{C1}$. In particular, as an application, we prove a variant of universality results regarding the smallest singular value of $M_{p,n}$. This paper is an extension of the results in \cite{tvcovariance} from the bulk of the spectrum up to the edge.

math.PR↗

arXiv2011

IRDC G030.88+00.13: A Tale of Two Massive Clumps

Massive stars (M $\gsim 10$ \msun) form from collapse of parsec-scale molecular clumps. How molecular clumps fragment to give rise to massive stars in a cluster with a distribution of masses is unclear. We search for cold cores that may lead to future formation of massive stars in a massive ($> 10^3$ \msun), low luminosity ($4.6 \times 10^2$ \lsun) infrared dark cloud (IRDC) G030.88+00.13. The \nh3 data from VLA and GBT reveal that the extinction feature seen in the infrared consists of two distinctive clumps along the same line of sight: The C1 clump at 97 \kms-1 coincides with the extinction in the Spitzer 8 and 24 $μ$m. Therefore, it is responsible for the majority of the IRDC. The C2 clump at 107 \kms-1 is more compact and has a peak temperature of 45 K. Compact dust cores and \h2O masers revealed in the SMA and VLA observations are mostly associated with C2, and none is within the IRDC in C1. The luminosity indicates that neither the C1 nor C2 clump has yet to form massive protostars. But C1 might be at a precluster forming stage. The simulated observations rule out 0.1pc cold cores with masses above 8 \msun\ within the IRDC. The core masses in C1 and C2, and those in high-mass protostellar objects suggest an evolutionary trend that the mass of cold cores increases over time. Based on our findings, we propose an empirical picture of massive star formation that protostellar cores and the embedded protostars undergo simultaneous mass growth during the protostellar evolution.

astro-ph.GA↗

arXiv2010

An Effective Clustering Approach to Web Query Log Anonymization

Web query log data contain information useful to research; however, release of such data can re-identify the search engine users issuing the queries. These privacy concerns go far beyond removing explicitly identifying information such as name and address, since non-identifying personal data can be combined with publicly available information to pinpoint to an individual. In this work we model web query logs as unstructured transaction data and present a novel transaction anonymization technique based on clustering and generalization techniques to achieve the k-anonymity privacy. We conduct extensive experiments on the AOL query log data. Our results show that this method results in a higher data utility compared to the state of-the-art transaction anonymization methods.

cs.DB↗

arXiv2010

Sparse random graphs: Eigenvalues and Eigenvectors

In this paper we prove the semi-circular law for the eigenvalues of regular random graph $G_{n,d}$ in the case $d\rightarrow \infty$, complementing a previous result of McKay for fixed $d$. We also obtain a upper bound on the infinity norm of eigenvectors of Erdős-Rényi random graph $G(n,p)$, answering a question raised by Dekel-Lee-Linial.

math.CO↗

arXiv2009

The relation between 13CO(2-1) line width in molecular clouds and bolometric luminosity of associated IRAS sources

We search for evidence of a relation between properties of young stellar objects (YSOs) and their parent molecular clouds to understand the initial conditions of high-mass star formation. A sample of 135 sources was selected from the Infrared Astronomical Satellite (IRAS) Point Source Catalog, on the basis of their red color to enhance the possibility of discovering young sources. Using the Kolner Observatorium fur SubMillimeter Astronomie (KOSMA) 3-m telescope, a single-point survey in 13CO(2-1) was carried out for the entire sample, and 14 sources were mapped further. Archival mid-infrared (MIR) data were compared with the 13CO emissions to identify evolutionary stages of the sources. A 13CO observed sample was assembled to investigate the correlation between 13CO line width of the clouds and the luminosity of the associated YSOs. We identified 98 sources suitable for star formation analyses for which relevant parameters were calculated. We detected 18 cores from 14 mapped sources, which were identified with eight pre-UC HII regions and one UC HII region, two high-mass cores earlier than pre-UC HII phase, four possible star forming clusters, and three sourceless cores. By compiling a large (360 sources) 13CO observed sample, a good correlation was found between the 13CO line width of the clouds and the bolometric luminosity of the associated YSOs, which can be fitted as a power law: lg(dV13/km/s)=-0.023+0.135lg(Lbol/Lsolar). Results show that luminous (>10^3Lsolar) YSOs tend to be associated with both more massive and more turbulent (dV13>2km/s) molecular cloud structures.

astro-ph.SR↗

arXiv2009

Anonymization with Worst-Case Distribution-Based Background Knowledge

Background knowledge is an important factor in privacy preserving data publishing. Distribution-based background knowledge is one of the well studied background knowledge. However, to the best of our knowledge, there is no existing work considering the distribution-based background knowledge in the worst case scenario, by which we mean that the adversary has accurate knowledge about the distribution of sensitive values according to some tuple attributes. Considering this worst case scenario is essential because we cannot overlook any breaching possibility. In this paper, we propose an algorithm to anonymize dataset in order to protect individual privacy by considering this background knowledge. We prove that the anonymized datasets generated by our proposed algorithm protects individual privacy. Our empirical studies show that our method preserves high utility for the published data at the same time.

cs.DB↗

arXiv2009

Can the Utility of Anonymized Data be used for Privacy Breaches?

Group based anonymization is the most widely studied approach for privacy preserving data publishing. This includes k-anonymity, l-diversity, and t-closeness, to name a few. The goal of this paper is to raise a fundamental issue on the privacy exposure of the current group based approach. This has been overlooked in the past. The group based anonymization approach basically hides each individual record behind a group to preserve data privacy. If not properly anonymized, patterns can actually be derived from the published data and be used by the adversary to breach individual privacy. For example, from the medical records released, if patterns such as people from certain countries rarely suffer from some disease can be derived, then the information can be used to imply linkage of other people in an anonymized group with this disease with higher likelihood. We call the derived patterns from the published data the foreground knowledge. This is in contrast to the background knowledge that the adversary may obtain from other channels as studied in some previous work. Finally, we show by experiments that the attack is realistic in the privacy benchmark dataset under the traditional group based anonymization approach.

cs.DB↗

arXiv2009

Preserving Individual Privacy in Serial Data Publishing

While previous works on privacy-preserving serial data publishing consider the scenario where sensitive values may persist over multiple data releases, we find that no previous work has sufficient protection provided for sensitive values that can change over time, which should be the more common case. In this work we propose to study the privacy guarantee for such transient sensitive values, which we call the global guarantee. We formally define the problem for achieving this guarantee and derive some theoretical properties for this problem. We show that the anonymized group sizes used in the data anonymization is a key factor in protecting individual privacy in serial publication. We propose two strategies for anonymization targeting at minimizing the average group size and the maximum group size. Finally, we conduct experiments on a medical dataset to show that our method is highly efficient and also produces published data of very high utility.

cs.DB↗