2 research outputs found
Tight bounds on the randomized communication complexity of symmetric XOR functions in one-way and SMP models
We study the communication complexity of symmetric XOR functions, namely
functions that can be
formulated as for some predicate , where is the Hamming weight of the bitwise
XOR of and . We give a public-coin randomized protocol in the
Simultaneous Message Passing (SMP) model, with the communication cost matching
the known lower bound for the \emph{quantum} and \emph{two-way} model up to a
logarithm factor. As a corollary, this closes a quadratic gap between quantum
lower bound and randomized upper bound for the one-way model, answering an open
question raised in Shi and Zhang \cite{SZ09}
Approximate -Sketching of Valuation Functions
We study the problem of constructing a linear sketch of minimum dimension
that allows approximation of a given real-valued function with small expected squared error. We
develop a general theory of linear sketching for such functions through which
we analyze their dimension for most commonly studied types of valuation
functions: additive, budget-additive, coverage, -Lipschitz submodular
and matroid rank functions. This gives a characterization of how many bits of
information have to be stored about the input so that one can compute
under additive updates to its coordinates.
Our results are tight in most cases and we also give extensions to the
distributional version of the problem where the input is
generated uniformly at random. Using known connections with dynamic streaming
algorithms, both upper and lower bounds on dimension obtained in our work
extend to the space complexity of algorithms evaluating under long
sequences of additive updates to the input presented as a stream. Similar
results hold for simultaneous communication in a distributed setting.Comment: To appear in RANDOM 201