Phenomenal Privacy, Similarity and Communicability

Communicability in complex networks.

We propose a new measure of the communicability of a complex network, which is a broad generalization of the concept of the shortest path. According to the new measure, most of the real-world networks display the largest communicability between the most connected (popular) nodes of the network (assortative communicability). There are also several networks with the disassortative communicability...

Privacy-preserving similarity coefficients for binary data

Similarity coefficients (also known as coefficients of association) are important measurement techniques used to quantify the extent to which objects resemble one another. Due to privacy concerns, the data owner might not want to participate in any similarity measurement if the original dataset will be revealed or could be derived from the final output. There are many different measurements use...

Efficient Privacy Preserving Protocols for Similarity Join

During the similarity join process, one or more sources may not allow sharing its data with other sources. In this case, a privacy preserving similarity join is required. We showed in our previous work [4] that using long attributes, such as paper abstracts, movie summaries, product descriptions, and user feedbacks, could improve the similarity join accuracy using supervised learning. However, ...

Perception Preattentive and Phenomenal

Recent work in experimental psychology and neuroscience has revealed a rather surprising architecture for early (or preattentive) perceptual processes. This paper will describe some of the surprising features of that architecture, and how they bear on recent philosophical debates about the notion of phenomenal consciousness. I will argue that the common sense idea that states of phenomenal cons...

Indiscriminability and the Phenomenal