New bounds on classical and quantum one-way communication complexity
Rahul Jain, Shengyu Zhang

TL;DR
This paper establishes new bounds on classical and quantum one-way communication complexity for various functions and distributions, extending previous results and providing lower bounds in the quantum setting.
Contribution
It extends classical bounds to non-product distributions and introduces quantum lower bounds based on rectangle bounds for total and partial functions.
Findings
Classical bounds incorporate non-product distributions and relate to VC dimension and mutual information.
Quantum bounds relate quantum complexity to rectangle bounds under product distributions.
Results apply to both boolean and non-boolean functions, total and partial, with explicit error parameters.
Abstract
In this paper we provide new bounds on classical and quantum distributional communication complexity in the two-party, one-way model of communication. In the classical model, our bound extends the well known upper bound of Kremer, Nisan and Ron to include non-product distributions. We show that for a boolean function f:X x Y -> {0,1} and a non-product distribution mu on X x Y and epsilon in (0,1/2) constant: D_{epsilon}^{1, mu}(f)= O((I(X:Y)+1) vc(f)), where D_{epsilon}^{1, mu}(f) represents the one-way distributional communication complexity of f with error at most epsilon under mu; vc(f) represents the Vapnik-Chervonenkis dimension of f and I(X:Y) represents the mutual information, under mu, between the random inputs of the two parties. For a non-boolean function f:X x Y ->[k], we show a similar upper bound on D_{epsilon}^{1, mu}(f) in terms of k, I(X:Y) and the pseudo-dimension of f'…
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Taxonomy
TopicsComplexity and Algorithms in Graphs · Machine Learning and Algorithms · Stochastic Gradient Optimization Techniques
