935 research outputs found
Lifting Theorems Meet Information Complexity: Known and New Lower Bounds of Set-disjointness
Set-disjointness problems are one of the most fundamental problems in
communication complexity and have been extensively studied in past decades.
Given its importance, many lower bound techniques were introduced to prove
communication lower bounds of set-disjointness. Combining ideas from
information complexity and query-to-communication lifting theorems, we
introduce a density increment argument to prove communication lower bounds for
set-disjointness:
We give a simple proof showing that a large rectangle cannot be
-monochromatic for multi-party unique-disjointness.
We interpret the direct-sum argument as a density increment process and give
an alternative proof of randomized communication lower bounds for multi-party
unique-disjointness.
Avoiding full simulations in lifting theorems, we simplify and improve
communication lower bounds for sparse unique-disjointness.
Potential applications to be unified and improved by our density increment
argument are also discussed.Comment: Working Pape
Trading Information Complexity for Error
We consider the standard two-party communication model. The central problem studied in this article is how much can one save in information complexity by allowing a certain error.
* For arbitrary functions, we obtain lower bounds and upper bounds indicating a gain that is of order Omega(h(epsilon)) and O(h(sqrt{epsilon})). Here h denotes the binary entropy function.
* We analyze the case of the two-bit AND function in detail to show that for this function the gain is Theta(h(epsilon)). This answers a question of Braverman et al. [Braverman, STOC 2013].
* We obtain sharp bounds for the set disjointness function of order n. For the case of the distributional error, we introduce a new protocol that achieves a gain of Theta(sqrt{h(epsilon)}) provided that n is sufficiently large. We apply these results to answer another of question of Braverman et al. regarding the randomized communication complexity of the set disjointness function.
* Answering a question of Braverman [Braverman, STOC 2012], we apply our analysis of the set disjointness function to establish a gap between the two different notions of the prior-free information cost. In light of [Braverman, STOC 2012], this implies that amortized randomized communication complexity is not necessarily equal to the amortized distributional communication complexity with respect to the hardest distribution.
As a consequence, we show that the epsilon-error randomized communication complexity of the set disjointness function of order n is n[C_{DISJ} - Theta(h(epsilon))] + o(n), where C_{DISJ} ~ 0.4827$ is the constant found by Braverman et al. [Braverman, STOC 2012]
Simplified Lower Bounds on the Multiparty Communication Complexity of Disjointness
We show that the deterministic number-on-forehead communication complexity of set disjointness for k parties on a universe of size n is Omega(n/4^k). This gives the first lower bound that is linear in n, nearly matching Grolmusz\u27s upper bound of O(log^2(n) + k^2n/2^k). We also simplify the proof of Sherstov\u27s Omega(sqrt(n)/(k2^k)) lower bound for the randomized communication complexity of set disjointness
The Complexity of Quantum Disjointness
We introduce the communication problem QNDISJ, short for Quantum (Unique) Non-Disjointness, and study its complexity under different modes of communication complexity. The main motivation for the problem is that it is a candidate for the separation of the quantum communication complexity classes QMA and QCMA. The problem generalizes the Vector-in-Subspace and Non-Disjointness problems. We give tight bounds for the QMA, quantum, randomized communication complexities of the problem. We show polynomially related upper and lower bounds for the MA complexity. We also show an upper bound for QCMA protocols, and show that the bound is tight for a natural class of QCMA protocols for the problem. The latter lower bound is based on a geometric lemma, that states that every subset of the n-dimensional sphere of measure 2^-p must contain an ortho-normal set of points of size Omega(n/p).
We also study a "small-spaces" version of the problem, and give upper and lower bounds for its randomized complexity that show that the QNDISJ problem is harder than Non-disjointness for randomized protocols. Interestingly, for quantum modes the complexity depends only on the dimension of the smaller space, whereas for classical modes the dimension of the larger space matters
Communication Complexity of Set-Disjointness for All Probabilities
We study set-disjointness in a generalized model of randomized two-party communication where the probability of acceptance must be at least alpha(n) on yes-inputs and at most beta(n) on no-inputs, for some functions alpha(n)>beta(n). Our main result is a complete characterization of the private-coin communication complexity of set-disjointness for all functions alpha and beta, and a near-complete characterization for public-coin protocols. In particular, we obtain a simple proof of a theorem of Braverman and Moitra (STOC 2013), who studied the case where alpha=1/2+epsilon(n) and beta=1/2-epsilon(n). The following contributions play a crucial role in our characterization and are interesting in their own right.
(1) We introduce two communication analogues of the classical complexity class that captures small bounded-error computations: we define a "restricted" class SBP (which lies between MA and AM) and an "unrestricted" class USBP. The distinction between them is analogous to the distinction between the well-known communication classes PP and UPP.
(2) We show that the SBP communication complexity is precisely captured by the classical corruption lower bound method. This sharpens a theorem of Klauck (CCC 2003).
(3) We use information complexity arguments to prove a linear lower bound on the USBP complexity of set-disjointness
Information complexity of the AND function in the two-Party, and multiparty settings
In a recent breakthrough paper [M. Braverman, A. Garg, D. Pankratov, and O.
Weinstein, From information to exact communication, STOC'13] Braverman et al.
developed a local characterization for the zero-error information complexity in
the two party model, and used it to compute the exact internal and external
information complexity of the 2-bit AND function, which was then applied to
determine the exact asymptotic of randomized communication complexity of the
set disjointness problem.
In this article, we extend their results on AND function to the multi-party
number-in-hand model by proving that the generalization of their protocol has
optimal internal and external information cost for certain distributions. Our
proof has new components, and in particular it fixes some minor gaps in the
proof of Braverman et al
On the communication complexity of sparse set disjointness and exists-equal problems
In this paper we study the two player randomized communication complexity of
the sparse set disjointness and the exists-equal problems and give matching
lower and upper bounds (up to constant factors) for any number of rounds for
both of these problems. In the sparse set disjointness problem, each player
receives a k-subset of [m] and the goal is to determine whether the sets
intersect. For this problem, we give a protocol that communicates a total of
O(k\log^{(r)}k) bits over r rounds and errs with very small probability. Here
we can take r=\log^{*}k to obtain a O(k) total communication \log^{*}k-round
protocol with exponentially small error probability, improving on the O(k)-bits
O(\log k)-round constant error probability protocol of Hastad and Wigderson
from 1997.
In the exist-equal problem, the players receive vectors x,y\in [t]^n and the
goal is to determine whether there exists a coordinate i such that x_i=y_i.
Namely, the exists-equal problem is the OR of n equality problems. Observe that
exists-equal is an instance of sparse set disjointness with k=n, hence the
protocol above applies here as well, giving an O(n\log^{(r)}n) upper bound. Our
main technical contribution in this paper is a matching lower bound: we show
that when t=\Omega(n), any r-round randomized protocol for the exists-equal
problem with error probability at most 1/3 should have a message of size
\Omega(n\log^{(r)}n). Our lower bound holds even for super-constant r <=
\log^*n, showing that any O(n) bits exists-equal protocol should have \log^*n -
O(1) rounds
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