A distribution D over Σ1× ⋯ ×Σ n is called (non-uniform) k-wise independent if for any set of k indices {i 1, ..., i k } and for any z1zki1ik, PrXD[Xi1Xik=z1zk]=PrXD[Xi1=z1]PrXD[Xik=zk]. We study the problem of testing (non-uniform) k-wise independent distributions over product spaces. For the uniform case we show an upper bound on the distance between a distribution D from the set of k-wise independent distributions in terms of the sum of Fourier coefficients of D at vectors of weight at most k. Such a bound was previously known only for the binary field. For the non-uniform case, we give a new characterization of distributions being k-wise independent and further show that such a characterization is robust. These greatly generalize the re...
AbstractThe algorithmic theory of randomness is well developed when the underlying space is the set ...
We study the problem of testing discrete distributions with a focus on the high probability regime. ...
AbstractThe algorithmic theory of randomness is well developed when the underlying space is the set ...
A discrete distribution D over Σ1 × · · · × Σn is called (non-uniform) k-wise independent if for...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer...
A probability distribution over {0, 1}n is k-wise independent if its restriction to any k coordinate...
In this work, we consider the problems of testing whether a distribution over{0, 1} n is k-wise or (...
In this work, we consider the problems of testing whether a distribution over {0, 1} n is k-wise (re...
A probability distribution over {-1, 1}^n is (epsilon, k)-wise uniform if, roughly, it is epsilon-cl...
Given access to independent samples of a distribution A over [n] × [m], we show how to test whether ...
Given access to independent samples of a distribution A over [n] × [m], we show how to test whether ...
Given access to independent samples of a distribution A over [n] × [m], we show how to test whether ...
Given access to independent samples of a distributionA over [n] [m], we show how to test whether th...
Distribution testing deals with what information can be deduced about an unknown distribution over $...
The algorithmic theory of randomness is well developed when the underlying space is the set of finit...
AbstractThe algorithmic theory of randomness is well developed when the underlying space is the set ...
We study the problem of testing discrete distributions with a focus on the high probability regime. ...
AbstractThe algorithmic theory of randomness is well developed when the underlying space is the set ...
A discrete distribution D over Σ1 × · · · × Σn is called (non-uniform) k-wise independent if for...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer...
A probability distribution over {0, 1}n is k-wise independent if its restriction to any k coordinate...
In this work, we consider the problems of testing whether a distribution over{0, 1} n is k-wise or (...
In this work, we consider the problems of testing whether a distribution over {0, 1} n is k-wise (re...
A probability distribution over {-1, 1}^n is (epsilon, k)-wise uniform if, roughly, it is epsilon-cl...
Given access to independent samples of a distribution A over [n] × [m], we show how to test whether ...
Given access to independent samples of a distribution A over [n] × [m], we show how to test whether ...
Given access to independent samples of a distribution A over [n] × [m], we show how to test whether ...
Given access to independent samples of a distributionA over [n] [m], we show how to test whether th...
Distribution testing deals with what information can be deduced about an unknown distribution over $...
The algorithmic theory of randomness is well developed when the underlying space is the set of finit...
AbstractThe algorithmic theory of randomness is well developed when the underlying space is the set ...
We study the problem of testing discrete distributions with a focus on the high probability regime. ...
AbstractThe algorithmic theory of randomness is well developed when the underlying space is the set ...