Gap Hamming Distance is a well-studied problem in communication complexity, in which Alice and Bob have to decide whether the Hamming distance between their respective n-bit inputs is less than n/2 - √n or greater than n/2 + √n. We show that every k-round bounded-error communication protocol for this problem sends a message of at least Ω(n/(k²logk)) bits. This lower bound has an exponentially better dependence on the number of rounds than the previous best bound, due to Brody and Chakrabarti. Our communication lower bound implies strong space lower bounds on algorithms for a number of data stream computations, such as approximating the number of distinct elements in a stream
The Hamming distance function Hamn,d returns 1 on all pairs of inputs x and y that dier in at most d...
We consider the problem of computing a (1+epsilon)-approximation of the Hamming distance between a p...
We study the communication complexity of evaluating functions when the input data is randomly alloca...
Gap Hamming Distance is a well-studied problem in communication complexity, in which Alice and Bob h...
We prove an optimal Ω(n) lower bound on the randomized communication complex- ity of the much-studie...
We prove an optimal Ω(n) lower bound on the randomized communication complex- ity of the much-studie...
Assume that Alice has a binary string x and Bob a binary string y, both strings are of length n. The...
We prove an optimal Ω(n) lower bound on the randomized communication complexity of the much-studied ...
We prove an optimal Ω(n) lower bound on the randomized communication complexity of the much-studied ...
International audienceWe prove an optimal Ω(n) lower bound on the randomized communication complexit...
International audienceWe prove an optimal Ω(n) lower bound on the randomized communication complexit...
International audienceWe prove an optimal $\Omega(n)$ lower bound on the randomized communication co...
The Hamming distance function Ham_{n,d} returns 1 on all pairs of inputs x and y that differ in at m...
The Hamming distance function Ham_{n,d} returns 1 on all pairs of inputs x and y that differ in at m...
We prove nearly matching upper and lower bounds on the randomized communication complexity of the fo...
The Hamming distance function Hamn,d returns 1 on all pairs of inputs x and y that dier in at most d...
We consider the problem of computing a (1+epsilon)-approximation of the Hamming distance between a p...
We study the communication complexity of evaluating functions when the input data is randomly alloca...
Gap Hamming Distance is a well-studied problem in communication complexity, in which Alice and Bob h...
We prove an optimal Ω(n) lower bound on the randomized communication complex- ity of the much-studie...
We prove an optimal Ω(n) lower bound on the randomized communication complex- ity of the much-studie...
Assume that Alice has a binary string x and Bob a binary string y, both strings are of length n. The...
We prove an optimal Ω(n) lower bound on the randomized communication complexity of the much-studied ...
We prove an optimal Ω(n) lower bound on the randomized communication complexity of the much-studied ...
International audienceWe prove an optimal Ω(n) lower bound on the randomized communication complexit...
International audienceWe prove an optimal Ω(n) lower bound on the randomized communication complexit...
International audienceWe prove an optimal $\Omega(n)$ lower bound on the randomized communication co...
The Hamming distance function Ham_{n,d} returns 1 on all pairs of inputs x and y that differ in at m...
The Hamming distance function Ham_{n,d} returns 1 on all pairs of inputs x and y that differ in at m...
We prove nearly matching upper and lower bounds on the randomized communication complexity of the fo...
The Hamming distance function Hamn,d returns 1 on all pairs of inputs x and y that dier in at most d...
We consider the problem of computing a (1+epsilon)-approximation of the Hamming distance between a p...
We study the communication complexity of evaluating functions when the input data is randomly alloca...