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Let $m$ be the number of stream records and $M$ be the largest magnitude of a stream update.\n  The algorithm uses space in bits $$ O(p^2\\epsilon^{-2}n^{1-2/p}E(p,n) \\log (n) \\log (nmM)/\\min(\\log (n),\\epsilon^{4/p-2}))$$ where, $E(p,n) = (1-2/p)^{-1}(1-n^{-4(1-2/p})$. Here $E(p,n)$ is $ O(1)$ for $p = 2+\\Omega(1)$ and $ O(\\log n)$ for $p = 2 + O(1/\\log (n)$. 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Let $m$ be the number of stream records and $M$ be the largest magnitude of a stream update.\n  The algorithm uses space in bits $$ O(p^2\\epsilon^{-2}n^{1-2/p}E(p,n) \\log (n) \\log (nmM)/\\min(\\log (n),\\epsilon^{4/p-2}))$$ where, $E(p,n) = (1-2/p)^{-1}(1-n^{-4(1-2/p})$. Here $E(p,n)$ is $ O(1)$ for $p = 2+\\Omega(1)$ and $ O(\\log n)$ for $p = 2 + O(1/\\log (n)$. 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