We prove nearly matching upper and lower bounds on the randomized communication complexity of the following problem: Alice and Bob are each given a probability distribution over n elements, and they wish to estimate within ±ϵ the statistical (total variation) distance between their distributions. For some range of parameters, there is up to a log n factor gap between the upper and lower bounds, and we identify a barrier to using information complexity techniques to improve the lower bound in this case. We also prove a side result that we discovered along the way: the randomized communication complexity of n-bit Majority composed with n-bit Greater-Than is O(n log n)
We prove an optimal Ω(n) lower bound on the randomized communication complex- ity of the much-studie...
The Hamming distance function Hamn,d returns 1 on all pairs of inputs x and y that dier in at most d...
Abstract-The communication complexity of a two-variable function f ( x, y) is the number of inform...
We prove nearly matching upper and lower bounds on the randomized communication complexity of the fo...
We prove nearly matching upper and lower bounds on the randomized communication complexity of the fo...
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...
We prove an optimal Ω(n) lower bound on the randomized communication complexity of the much-studied ...
International audienceWe prove an optimal $\Omega(n)$ lower bound on the randomized communication co...
In this paper we study the individual communication complexity of the following problem. Alice recei...
In this paper we study the individual communication complexity of the following problem. Alice recei...
We study the effect that the amount of correlation in a bipartite distribution has on the communicat...
© 2019 Association for Computing Machinery. We characterize the communication complexity of the foll...
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...
The Hamming distance function Hamn,d returns 1 on all pairs of inputs x and y that dier in at most d...
Abstract-The communication complexity of a two-variable function f ( x, y) is the number of inform...
We prove nearly matching upper and lower bounds on the randomized communication complexity of the fo...
We prove nearly matching upper and lower bounds on the randomized communication complexity of the fo...
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...
We prove an optimal Ω(n) lower bound on the randomized communication complexity of the much-studied ...
International audienceWe prove an optimal $\Omega(n)$ lower bound on the randomized communication co...
In this paper we study the individual communication complexity of the following problem. Alice recei...
In this paper we study the individual communication complexity of the following problem. Alice recei...
We study the effect that the amount of correlation in a bipartite distribution has on the communicat...
© 2019 Association for Computing Machinery. We characterize the communication complexity of the foll...
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...
The Hamming distance function Hamn,d returns 1 on all pairs of inputs x and y that dier in at most d...
Abstract-The communication complexity of a two-variable function f ( x, y) is the number of inform...