Add to ORKGWe give a one-pass, O~(m^{1-2/k})-space algorithm for estimating the k-th frequency moment of a data stream for any real k>2. Together with known lower bounds, this resolves the main problem left open by Alon, Matias, Szegedy, STOC'96. Our algorithm enables deletions as well as insertions of stream elements
We study the classical problem of moment estimation of an underlying vector whose $n$ coordinates ar...
We consider general update streams, where, the stream is a sequence of updates of the form $(index, ...
The problem of finding heavy hitters and approximating the frequencies of items is at the heart of m...
We give a one-pass, O~(m^{1-2/k})-space algorithm for estimating the k-th frequency moment of a data...
We give a 1-pass Õ(m1−2/k)-space algorithm for computing the k-th frequency moment of a data stream ...
In 1999 Alon et al. introduced the still active research topic of approximating the frequency moment...
In this paper we consider the problem of approximating frequency moments in the streaming model. Giv...
Let a data stream have length m over an alphabet of n letters, with letter i occurring m_i times for...
In this paper, we provide the first optimal algorithm for the remaining open question from the semin...
Recently, an extension of the standard data stream model has been introduced in which an algorithm c...
We consider the read/write streams model, an extension of the standard data stream model in which an...
Given a stream with frequency vector f in n dimensions, we characterize the space necessary for appr...
The frequency moments of a sequence containing mi elements of type i, for 1 i n, are the numbers Fk ...
We revisit one of the classic problems in the data stream literature, namely, that of estimating the...
AbstractThe frequency moments of a sequence containingmielements of typei, 1⩽i⩽n, are the numbersFk=...
We study the classical problem of moment estimation of an underlying vector whose $n$ coordinates ar...
We consider general update streams, where, the stream is a sequence of updates of the form $(index, ...
The problem of finding heavy hitters and approximating the frequencies of items is at the heart of m...
We give a one-pass, O~(m^{1-2/k})-space algorithm for estimating the k-th frequency moment of a data...
We give a 1-pass Õ(m1−2/k)-space algorithm for computing the k-th frequency moment of a data stream ...
In 1999 Alon et al. introduced the still active research topic of approximating the frequency moment...
In this paper we consider the problem of approximating frequency moments in the streaming model. Giv...
Let a data stream have length m over an alphabet of n letters, with letter i occurring m_i times for...
In this paper, we provide the first optimal algorithm for the remaining open question from the semin...
Recently, an extension of the standard data stream model has been introduced in which an algorithm c...
We consider the read/write streams model, an extension of the standard data stream model in which an...
Given a stream with frequency vector f in n dimensions, we characterize the space necessary for appr...
The frequency moments of a sequence containing mi elements of type i, for 1 i n, are the numbers Fk ...
We revisit one of the classic problems in the data stream literature, namely, that of estimating the...
AbstractThe frequency moments of a sequence containingmielements of typei, 1⩽i⩽n, are the numbersFk=...
We study the classical problem of moment estimation of an underlying vector whose $n$ coordinates ar...
We consider general update streams, where, the stream is a sequence of updates of the form $(index, ...
The problem of finding heavy hitters and approximating the frequencies of items is at the heart of m...