Learn More
Given a <i>d</i>-dimensional data set, a point <i>p</i> dominates another point <i>q</i> if it is better than or equal to <i>q</i> in all dimensions and better than <i>q</i> in at least one dimension. A point is a skyline point if there does not exists any point that can dominate it. Skyline queries, which return skyline points, are useful in many decision(More)
ϵ-differential privacy is the state-of-the-art model for releasing sensitive information while protecting privacy. Numerous methods have been proposed to enforce ϵ-differential privacy in various analytical tasks, e.g., regression analysis. Existing solutions for regression analysis, however, are either limited to non-standard types of regression or unable(More)
Available methods for differentiating human embryonic stem cells (ESCs) and induced pluripotent cells (iPSCs) into neurons are often cumbersome, slow, and variable. Alternatively, human fibroblasts can be directly converted into induced neuronal (iN) cells. However, with present techniques conversion is inefficient, synapse formation is limited, and only(More)
In many decision-making applications, the skyline query is frequently used to find a set of dominating data points (called skyline points) in a multi-dimensional dataset. In a high-dimensional space skyline points no longer offer any interesting insights as there are too many of them. In this paper, we introduce a novel metric, called skyline frequency that(More)
Members of the transmembrane AMPA receptor-regulatory protein (TARP) family modulate AMPA receptor (AMPA-R) trafficking and function. AMPA-Rs consist of four pore-forming subunits. Previous studies show that TARPs are an integral part of the AMPA-R complex, acting as accessory subunits for mature receptors in vivo. The TARP/AMPA-R stoichiometry was(More)
Differential privacy (DP) is a promising scheme for releasing the results of statistical queries on sensitive data, with strong privacy guarantees against adversaries with arbitrary background knowledge. Existing studies on differential privacy mostly focus on simple aggregations such as counts. This paper investigates the publication of DP-compliant(More)
Blockade of synaptic activity induces homeostatic plasticity, in part by stimulating synthesis of all-trans retinoic acid (RA), which in turn increases AMPA receptor synthesis. However, the synaptic signal that triggers RA synthesis remained unknown. Using multiple activity-blockade protocols that induce homeostatic synaptic plasticity, here we show that RA(More)
Moving object indexing and query processing is a well studied research topic, with applications in areas such as intelligent transport systems and location-based services. While much existing work explicitly or implicitly assumes a deterministic object movement model, real-world objects often move in more complex and stochastic ways. This paper investigates(More)
Strings are ubiquitous in computer systems and hence string processing has attracted extensive research effort from computer scientists in diverse areas. One of the most important problems in string processing is to efficiently evaluate the similarity between two strings based on a specified similarity measure. String similarity search is a fundamental(More)
Differential privacy is a promising privacy-preserving paradigm for statistical query processing over sensitive data. It works by injecting random noise into each query result, such that it is provably hard for the adversary to infer the presence or absence of any individual record from the published noisy results. The main objective in differentially(More)