23,527 research outputs found
A Reference Interpreter for the Graph Programming Language GP 2
GP 2 is an experimental programming language for computing by graph
transformation. An initial interpreter for GP 2, written in the functional
language Haskell, provides a concise and simply structured reference
implementation. Despite its simplicity, the performance of the interpreter is
sufficient for the comparative investigation of a range of test programs. It
also provides a platform for the development of more sophisticated
implementations.Comment: In Proceedings GaM 2015, arXiv:1504.0244
Lower and Upper Conditioning in Quantum Bayesian Theory
Updating a probability distribution in the light of new evidence is a very
basic operation in Bayesian probability theory. It is also known as state
revision or simply as conditioning. This paper recalls how locally updating a
joint state can equivalently be described via inference using the channel
extracted from the state (via disintegration). This paper also investigates the
quantum analogues of conditioning, and in particular the analogues of this
equivalence between updating a joint state and inference. The main finding is
that in order to obtain a similar equivalence, we have to distinguish two forms
of quantum conditioning, which we call lower and upper conditioning. They are
known from the literature, but the common framework in which we describe them
and the equivalence result are new.Comment: In Proceedings QPL 2018, arXiv:1901.0947
On the AdS Higher Spin / O(N) Vector Model Correspondence: degeneracy of the holographic image
We explore the conjectured duality between the critical O(N) vector model and
minimal bosonic massless higher spin (HS) theory in AdS. In the boundary free
theory, the conformal partial wave expansion (CPWE) of the four-point function
of the scalar singlet bilinear is reorganized to make it explicitly
crossing-symmetric and closed in the singlet sector, dual to the bulk HS gauge
fields. We are able to analytically establish the factorized form of the fusion
coefficients as well as the two-point function coefficient of the HS currents.
We insist in directly computing the free correlators from bulk graphs with the
unconventional branch. The three-point function of the scalar bilinear turns
out to be an "extremal" one at d=3. The four-leg bulk exchange graph can be
precisely related to the CPWs of the boundary dual scalar and its shadow. The
flow in the IR by Legendre transforming at leading 1/N, following the pattern
of double-trace deformations, and the assumption of degeneracy of the hologram
lead to the CPWE of the scalar four-point function at IR. Here we confirm some
previous results, obtained from more involved computations of skeleton graphs,
as well as extend some of them from d=3 to generic dimension 2<d<4.Comment: 22 pages, 5 figure
Algorithms and implementation of functional dependency discovery in XML : a thesis presented in partial fulfilment of the requirements for the degree of Master of Information Sciences in Information Systems at Massey University
1.1 Background Following the advent of the web, there has been a great demand for data interchange between applications using internet infrastructure. XML (extensible Markup Language) provides a structured representation of data empowered by broad adoption and easy deployment. As a subset of SGML (Standard Generalized Markup Language), XML has been standardized by the World Wide Web Consortium (W3C) [Bray et al., 2004], XML is becoming the prevalent data exchange format on the World Wide Web and increasingly significant in storing semi-structured data. After its initial release in 1996, it has evolved and been applied extensively in all fields where the exchange of structured documents in electronic form is required. As with the growing popularity of XML, the issue of functional dependency in XML has recently received well deserved attention. The driving force for the study of dependencies in XML is it is as crucial to XML schema design, as to relational database(RDB) design [Abiteboul et al., 1995]
Graph Laplacians and Stabilization of Vehicle Formations
Control of vehicle formations has emerged as a topic of significant interest to the controls community. In this paper, we merge tools from graph theory and control theory to derive stability criteria for formation stabilization. The interconnection between vehicles (i.e., which vehicles are sensed by other vehicles) is modeled as a graph, and the eigenvalues of the Laplacian matrix of the graph are used in stating a Nyquist-like stability criterion for vehicle formations. The location of the Laplacian eigenvalues can be correlated to the graph structure, and therefore used to identify desirable and undesirable formation interconnection topologies
Graphical modelling language for spycifying concurrency based on CSP
Introduced in this (shortened) paper is a graphical modelling language for specifying concurrency in software designs. The language notations are derived from CSP and the resulting designs form CSP diagrams. The notations reflect both data-flow and control-flow aspects of concurrent software architectures. These designs can automatically be described by CSP algebraic expressions that can be used for formal analysis. The designer does not have to be aware of the underlying mathematics. The techniques and rules presented provide guidance to the development of concurrent software architectures. One can detect and reason about compositional conflicts (errors in design), potential deadlocks (errors at run-time), and priority inversion problems (performance burden) at a high level of abstraction. The CSP diagram collaborates with objectoriented modelling languages and structured methods
Categorical Aspects of Parameter Learning
Parameter learning is the technique for obtaining the probabilistic
parameters in conditional probability tables in Bayesian networks from tables
with (observed) data --- where it is assumed that the underlying graphical
structure is known. There are basically two ways of doing so, referred to as
maximal likelihood estimation (MLE) and as Bayesian learning. This paper
provides a categorical analysis of these two techniques and describes them in
terms of basic properties of the multiset monad M, the distribution monad D and
the Giry monad G. In essence, learning is about the reltionships between
multisets (used for counting) on the one hand and probability distributions on
the other. These relationsips will be described as suitable natural
transformations
Security Toolbox for Detecting Novel and Sophisticated Android Malware
This paper presents a demo of our Security Toolbox to detect novel malware in
Android apps. This Toolbox is developed through our recent research project
funded by the DARPA Automated Program Analysis for Cybersecurity (APAC)
project. The adversarial challenge ("Red") teams in the DARPA APAC program are
tasked with designing sophisticated malware to test the bounds of malware
detection technology being developed by the research and development ("Blue")
teams. Our research group, a Blue team in the DARPA APAC program, proposed a
"human-in-the-loop program analysis" approach to detect malware given the
source or Java bytecode for an Android app. Our malware detection apparatus
consists of two components: a general-purpose program analysis platform called
Atlas, and a Security Toolbox built on the Atlas platform. This paper describes
the major design goals, the Toolbox components to achieve the goals, and the
workflow for auditing Android apps. The accompanying video
(http://youtu.be/WhcoAX3HiNU) illustrates features of the Toolbox through a
live audit.Comment: 4 pages, 1 listing, 2 figure
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