Sankara Muthukrishnan

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How does one deal with massive data sets that is available for analyses? We will describe the classical data stream model in which we make one pass over the data and with sublinear resources perform much of the data analyses we care about, such as frequent items, summaries, compressed sensing, clustering and others. We will present the basic algorithmic(More)
In the recent years, with an increase in the awareness of internet usage, there has been an explosion of data on the web. Huge amount of data resides on the web and of late there has been an increased necessity for search engines that retrieve documents and images, at least close to the search criteria if not exactly. The problem of retrieving near(More)
Inherent in the operation of many decision support and continuous referral systems is the notion of the \innuence" of a data point on the database. This notion arises in examples such as nding the set of customers aaected by the opening of a new store outlet location, notifying the subset of subscribers to a digital library who will nd a newly added(More)
Though it is known that clos interconnection networks have many advantages over the other interconnection networks, it would be interesting to see the performance benefits that clos networks can bring to the real world applications. In this paper, we compare the performance of Fast Fourier Transforms (FFT) in clos networks with that of in mesh networks, a(More)
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