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The problem of publishing privacy-guaranteed data for hypothesis testing is studied using the maximal leakage (ML) as a metric for privacy and the type-II error exponent as the utility metric. The optimal mechanism (random mapping) that maximizes utility for a bounded leakage guarantee is determined for the entire leakage range for binary datasets. For non-binary datasets, approximations in the high...
With the prosperity and popularity of social tagging communities, developing an enormous amount of user-generated data with modalities has emerged in recent years. Personalized search based on tag-based profiles, an indispensable and prominent way to assist users to access and retrieve their interested resources, has been extensively studied by research communities. In this paper, we revisit the extant...
A family of techniques in physics known as statistical mechanics is useful for describing the macroscopic properties of materials composed of a large (Avogadro's # ≈ 1024) number of atoms. This talk applies the same approach to the analysis of big data problems. The initial problem examined is that of classification, specifically binary hypothesis testing, in the big data, high dimensional scenario...
Location-based services (LBS) are widely deployed. When the implementation of an LBS-enabled service has evolved, regression testing can be employed to assure the previously established behaviors not having been adversely affected. Proper test case prioritization helps reveal service anomalies efficiently so that fixes can be scheduled earlier to minimize the nuisance to service consumers. A key observation...
The observed measuring processes are sampled by a multiplex measuring system based at the adaptive commutation principle. The object state numerical reflecting unit processes non-redundant samples. The numerical procedure makes it possible to yield a concrete number associated with its vector presentation. The information uncertainty numerical coding algorithm and its practical realization have been...
Information captured in software execution profiles can benefit verification activities by supporting more cost-effective fault localization and execution classification. This paper proposes an experimental design which utilizes execution information to quantify the effect of factors such as different programs and fault inclusions on the distinction between passed and failed execution profiles. For...
Manufacturing test data is often analyzed with the direct goal of increasing production yields and reduction of variance within the product. Six Sigma and statistical process control methodologies are the standard tool sets for analysis of test data. The normal course of events results in the analyst seeking to reduce failures by taking steps to correct the tests that fail most often. Unfortunately,...
Research on quality evaluating of fusion images is meaningful to improve the registration technology and fusion algorithms. The objective assessment metrics based on fusion image itself can not show comprehensively the fusion image quality, which could be incongruent against human eye response. Provide a new assessment method for fusion image quality by means of building artificial neural network...
Dynamic service compositions pose new verification and validation challenges such as uncertainty in service membership. Moreover, applying an entire test suite to loosely coupled services one after another in the same composition can be too rigid and restrictive. In this paper, we investigate the impact of service selection on service-centric testing techniques. Specifically, we propose to incorporate...
Location based services personalize their behaviors based on location data. When data kept by a service have evolved or the code has been modified, regression testing can be employed to assure the quality of services. Frequent data update however may lead to frequent regression testing and any faulty implementation of a service may affect many service consumers. Proper test case prioritization helps...
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