126,839 research outputs found
Dynamic Programming for Graphs on Surfaces
We provide a framework for the design and analysis of dynamic programming
algorithms for surface-embedded graphs on n vertices and branchwidth at most k.
Our technique applies to general families of problems where standard dynamic
programming runs in 2^{O(k log k)} n steps. Our approach combines tools from
topological graph theory and analytic combinatorics. In particular, we
introduce a new type of branch decomposition called "surface cut
decomposition", generalizing sphere cut decompositions of planar graphs
introduced by Seymour and Thomas, which has nice combinatorial properties.
Namely, the number of partial solutions that can be arranged on a surface cut
decomposition can be upper-bounded by the number of non-crossing partitions on
surfaces with boundary. It follows that partial solutions can be represented by
a single-exponential (in the branchwidth k) number of configurations. This
proves that, when applied on surface cut decompositions, dynamic programming
runs in 2^{O(k)} n steps. That way, we considerably extend the class of
problems that can be solved in running times with a single-exponential
dependence on branchwidth and unify/improve most previous results in this
direction.Comment: 28 pages, 3 figure
Extended Combinatorial Constructions for Peer-to-peer User-Private Information Retrieval
We consider user-private information retrieval (UPIR), an interesting
alternative to private information retrieval (PIR) introduced by Domingo-Ferrer
et al. In UPIR, the database knows which records have been retrieved, but does
not know the identity of the query issuer. The goal of UPIR is to disguise user
profiles from the database. Domingo-Ferrer et al.\ focus on using a
peer-to-peer community to construct a UPIR scheme, which we term P2P UPIR. In
this paper, we establish a strengthened model for P2P UPIR and clarify the
privacy goals of such schemes using standard terminology from the field of
privacy research. In particular, we argue that any solution providing privacy
against the database should attempt to minimize any corresponding loss of
privacy against other users. We give an analysis of existing schemes, including
a new attack by the database. Finally, we introduce and analyze two new
protocols. Whereas previous work focuses on a special type of combinatorial
design known as a configuration, our protocols make use of more general
designs. This allows for flexibility in protocol set-up, allowing for a choice
between having a dynamic scheme (in which users are permitted to enter and
leave the system), or providing increased privacy against other users.Comment: Updated version, which reflects reviewer comments and includes
expanded explanations throughout. Paper is accepted for publication by
Advances in Mathematics of Communication
Distance-based exponential probability models on constrained combinatorial optimization problems
Estimation of distribution algorithms have already demonstrated their utility when solving a broad range of combinatorial problems. However, there is still room for methodological improvements when approaching constrained type problems. The great majority of works in the literature implement external repairing or penalty schemes, or use ad-hoc sampling methods in order to avoid unfeasible solutions. In this work, we present a new way to develop EDAs for this type of problems by implementing distance-based exponential probability models defined exclusively on the set of feasible solutions. In order to illustrate this procedure, we take the 2-partition balanced Graph Partitioning Problem as a case of study, and design efficient learning and sampling methods in order to use these distance-based probability models in EDAs
Equiangular Tight Frames from Group Divisible Designs
An equiangular tight frame (ETF) is a type of optimal packing of lines in a real or complex Hilbert space. In the complex case, the existence of an ETF of a given size remains an open problem in many cases. In this paper, we observe that many of the known constructions of ETFs are of one of two types. We further provide a new method for combining a given ETF of one of these two types with an appropriate group divisible design (GDD) in order to produce a larger ETF of the same type. By applying this method to known families of ETFs and GDDs, we obtain several new infinite families of ETFs. The real instances of these ETFs correspond to several new infinite families of strongly regular graphs. Our approach was inspired by a seminal paper of Davis and Jedwab which both unified and generalized McFarland and Spence difference sets. We provide combinatorial analogs of their algebraic results, unifying Steiner ETFs with hyperoval ETFs and Tremain ETFs
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GENUS : a generic component library for high level synthesis
This report describes the organization of GENUS, a generic component library for high level synthesis. Generic components and instances in GENUS are organized into hierarchical classes, with the component type stored at the root of the hierarchy, and particular instances stored at the leaves. This permits a consistent representation of generic components which may be used by a variety of synthesis and analysis tools. The appendix contains the description of the GENUS generator library
Equiangular tight frames from group divisible designs
An equiangular tight frame (ETF) is a type of optimal packing of lines in a
real or complex Hilbert space. In the complex case, the existence of an ETF of
a given size remains an open problem in many cases. In this paper, we observe
that many of the known constructions of ETFs are of one of two types. We
further provide a new method for combining a given ETF of one of these two
types with an appropriate group divisible design (GDD) in order to produce a
larger ETF of the same type. By applying this method to known families of ETFs
and GDDs, we obtain several new infinite families of ETFs. The real instances
of these ETFs correspond to several new infinite families of strongly regular
graphs. Our approach was inspired by a seminal paper of Davis and Jedwab which
both unified and generalized McFarland and Spence difference sets. We provide
combinatorial analogs of their algebraic results, unifying Steiner ETFs with
hyperoval ETFs and Tremain ETFs
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