842 research outputs found
Provenance Views for Module Privacy
Scientific workflow systems increasingly store provenance information about
the module executions used to produce a data item, as well as the parameter
settings and intermediate data items passed between module executions. However,
authors/owners of workflows may wish to keep some of this information
confidential. In particular, a module may be proprietary, and users should not
be able to infer its behavior by seeing mappings between all data inputs and
outputs. The problem we address in this paper is the following: Given a
workflow, abstractly modeled by a relation R, a privacy requirement \Gamma and
costs associated with data. The owner of the workflow decides which data
(attributes) to hide, and provides the user with a view R' which is the
projection of R over attributes which have not been hidden. The goal is to
minimize the cost of hidden data while guaranteeing that individual modules are
\Gamma -private. We call this the "secureview" problem. We formally define the
problem, study its complexity, and offer algorithmic solutions
Informational Substitutes
We propose definitions of substitutes and complements for pieces of
information ("signals") in the context of a decision or optimization problem,
with game-theoretic and algorithmic applications. In a game-theoretic context,
substitutes capture diminishing marginal value of information to a rational
decision maker. We use the definitions to address the question of how and when
information is aggregated in prediction markets. Substitutes characterize
"best-possible" equilibria with immediate information aggregation, while
complements characterize "worst-possible", delayed aggregation. Game-theoretic
applications also include settings such as crowdsourcing contests and Q\&A
forums. In an algorithmic context, where substitutes capture diminishing
marginal improvement of information to an optimization problem, substitutes
imply efficient approximation algorithms for a very general class of (adaptive)
information acquisition problems.
In tandem with these broad applications, we examine the structure and design
of informational substitutes and complements. They have equivalent, intuitive
definitions from disparate perspectives: submodularity, geometry, and
information theory. We also consider the design of scoring rules or
optimization problems so as to encourage substitutability or complementarity,
with positive and negative results. Taken as a whole, the results give some
evidence that, in parallel with substitutable items, informational substitutes
play a natural conceptual and formal role in game theory and algorithms.Comment: Full version of FOCS 2016 paper. Single-column, 61 pages (48 main
text, 13 references and appendix
Computational complexity of the landscape I
We study the computational complexity of the physical problem of finding
vacua of string theory which agree with data, such as the cosmological
constant, and show that such problems are typically NP hard. In particular, we
prove that in the Bousso-Polchinski model, the problem is NP complete. We
discuss the issues this raises and the possibility that, even if we were to
find compelling evidence that some vacuum of string theory describes our
universe, we might never be able to find that vacuum explicitly.
In a companion paper, we apply this point of view to the question of how
early cosmology might select a vacuum.Comment: JHEP3 Latex, 53 pp, 2 .eps figure
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