Add to ORKGIn this paper we consider the problem of approximating frequency moments in the streaming model. Given a stream D = {p1, p2,..., pm} of numbers from {1,..., n}, a frequency of i is defined as fi = |{j: pj = i}|. The k-th frequency moment of D is defined as Fk = ∑n i=1
The exact computation of the number of distinct elements (frequency moment F0) is a fundamental prob...
International audienceWe investigate the problem of estimating on the fly the frequency at which ite...
We study the classical problem of moment estimation of an underlying vector whose $n$ coordinates ar...
We give a one-pass, O~(m^{1-2/k})-space algorithm for estimating the k-th frequency moment of a data...
Recently, an extension of the standard data stream model has been introduced in which an algorithm c...
In this paper, we provide the first optimal algorithm for the remaining open question from the semin...
We consider the read/write streams model, an extension of the standard data stream model in which an...
In 1999 Alon et al. introduced the still active research topic of approximating the frequency moment...
We revisit one of the classic problems in the data stream literature, namely, that of estimating the...
We give a 1-pass Õ(m1−2/k)-space algorithm for computing the k-th frequency moment of a data stream ...
Let a data stream have length m over an alphabet of n letters, with letter i occurring m_i times for...
Given a stream with frequency vector f in n dimensions, we characterize the space necessary for appr...
We consider the problem of approximating the frequency of frequently occurring elements in a stream...
We present algorithms for computing frequency counts exceeding a user-specified threshold over data ...
ABSTRACT. We consider the problem of approximating the frequency of frequently occuring elements in ...
The exact computation of the number of distinct elements (frequency moment F0) is a fundamental prob...
International audienceWe investigate the problem of estimating on the fly the frequency at which ite...
We study the classical problem of moment estimation of an underlying vector whose $n$ coordinates ar...
We give a one-pass, O~(m^{1-2/k})-space algorithm for estimating the k-th frequency moment of a data...
Recently, an extension of the standard data stream model has been introduced in which an algorithm c...
In this paper, we provide the first optimal algorithm for the remaining open question from the semin...
We consider the read/write streams model, an extension of the standard data stream model in which an...
In 1999 Alon et al. introduced the still active research topic of approximating the frequency moment...
We revisit one of the classic problems in the data stream literature, namely, that of estimating the...
We give a 1-pass Õ(m1−2/k)-space algorithm for computing the k-th frequency moment of a data stream ...
Let a data stream have length m over an alphabet of n letters, with letter i occurring m_i times for...
Given a stream with frequency vector f in n dimensions, we characterize the space necessary for appr...
We consider the problem of approximating the frequency of frequently occurring elements in a stream...
We present algorithms for computing frequency counts exceeding a user-specified threshold over data ...
ABSTRACT. We consider the problem of approximating the frequency of frequently occuring elements in ...
The exact computation of the number of distinct elements (frequency moment F0) is a fundamental prob...
International audienceWe investigate the problem of estimating on the fly the frequency at which ite...
We study the classical problem of moment estimation of an underlying vector whose $n$ coordinates ar...