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Hidden-Markov program algebra with iteration

ANNABELLE MCIVER, LARISSA MEINICKE, CARROLL MORGAN
2014 Mathematical Structures in Computer Science  
We use Hidden Markov Models to motivate a quantitative compositional semantics for noninterference-based security with iteration, including a refinement- or "implements" relation that compares two programs  ...  with respect to their information leakage; and we propose a program algebra for source-level reasoning about such programs, in particular as a means of establishing that an "implementation" program leaks  ...  The right-hand program is a refinement of the left-hand one because it is more secure; with an appropriate security-refinement algebra we would show this syntactically ( §9.3). 3 Hidden Markov models and  ... 
doi:10.1017/s0960129513000625 fatcat:si5oy4w2w5gjzmd4m543c27ajm

Page 298 of The Journal of the Operational Research Society Vol. 54, Issue 3 [page]

2003 The Journal of the Operational Research Society  
Iterative Solution Methods. Cambridge University Press: Cambridge, UK. Chvatal V (1983). Linear Programming. Freeman: New York. 3 Ching W (2002), Manufacturing systems with fuzzy backlog cost.  ...  Hidden Markov and Other Models for Discrete-valued Time Series. Chapman & Hall: London. 7 Ching WK, Fung ES and Ng M (2003).  ... 

Enabling access-privacy for random walk based data analysis applications

Ping Lin, K. Selçuk Candan
2007 Data & Knowledge Engineering  
In this paper, we focus on access-privacy enabled outsourced Markov chain based data analysis applications, where a non-trusted service provider takes (hidden) user queries that are described in terms  ...  We show that this iterative process can leak information regarding the possible values of the hidden input if the server has a priori knowledge about the underlying Markovian process.  ...  In [4] , we introduced an encryption scheme for execution of encrypted linear algebraic programs (on matrices) with conditions and loops.  ... 
doi:10.1016/j.datak.2007.03.011 fatcat:lamxyvpvpnbt5dtfh2jxi3vy2i

Access-Private Outsourcing of Markov Chain and RandomWalk based Data Analysis Applications

Ping Lin, K.S. Candan
2006 22nd International Conference on Data Engineering Workshops (ICDEW'06)  
In this paper, we focus on access-privacy enabled outsourced Markov chain based data analysis applications, where a non-trusted service provider takes (hidden) user queries that are described in terms  ...  We show that this iterative process can leak information regarding the possible values of the hidden input if the server has a priori knowledge about the underlying Markovian process.  ...  In [3] , we introduced an encryption scheme for execution of encrypted linear algebraic programs (on matrices) with conditions and loops.  ... 
doi:10.1109/icdew.2006.25 dblp:conf/icde/LinC06a fatcat:wnwaouu3mbeqhopzsshha7yjxe

Wind-tree model for billiard motion from a signal processing viewpoint [article]

Enrico Au-Yeung, Nick Kreissler
2021 arXiv   pre-print
We describe the phenomenon of the long-term trajectories by using a 3-state hidden Markov model.  ...  In the Ehrenfest wind tree model, a point particle moves on the plane and collides with randomly placed fixed square obstacles under the usual law of geometric optics.  ...  We assume no knowledge of algebraic topology. Instead, we take a signal processing viewpoint and use a hidden Markov model with three hidden states to study the phenomenon we observe.  ... 
arXiv:2107.04718v1 fatcat:s5nosvd4ejc35lieqcikw5yu5i

TIPPtool: Compositional Specification and Analysis of Markovian Performance Models [chapter]

H. Hermanns, V. Mertsiotakis, M. Siegle
1999 Lecture Notes in Computer Science  
In this short paper we briefly describe a tool which is based on a Markovian stochastic process algebra.  ...  We used the programming language Standard ML for implementing the parser, the semantics, the bisimulation algorithms and for the approximate Markov chain solution methods.  ...  In particular, internal (or hidden) immediate actions are assumed to happen immediately when enabled.  ... 
doi:10.1007/3-540-48683-6_42 fatcat:rmc24nctvfdppf6qpkhbv5ddoi

zipHMMlib: a highly optimised HMM library exploiting repetitions in the input to speed up the forward algorithm

Andreas Sand, Martin Kristiansen, Christian NS Pedersen, Thomas Mailund
2013 BMC Bioinformatics  
Background Hidden Markov models (HMMs) are a class of statistical models for sequential data with an underlying hidden structure.  ...  Hidden Markov models are widely used for genome analysis as they combine ease of modelling with efficient analysis algorithms.  ...  whole-genome analysis with a reasonably complex hidden Markov model.  ... 
doi:10.1186/1471-2105-14-339 pmid:24266924 pmcid:PMC4222747 fatcat:ys3rxxx7vrdfxfayn6lq4jymmq

Preface to the special issue on quantitative information flow

MIGUEL E. ANDRÉS, CATUSCIA PALAMIDESSI, GEOFFREY SMITH
2014 Mathematical Structures in Computer Science  
Papers with a foundational focus include those of  ...  A basic example is a login program -whenever it rejects an incorrect password, it unavoidably reveals that the secret password differs from the one that was entered.  ...  In Hidden-Markov Program Algebra with Iteration, McIver, Meinicke and Morgan introduce a quantitative compositional semantics for programs with iteration, and a notion of refinement which compares two  ... 
doi:10.1017/s0960129513000583 fatcat:ev7diiuwwvfi5czc7yz6jcrgxu

On Determining the Order of Markov Dependence of an Observed Process Governed by a Hidden Markov Model

R.J. Boys, D.A. Henderson
2002 Scientific Programming  
It extends previous work on homogeneous Markov chains to more general and applicable hidden Markov models.  ...  This paper describes a Bayesian approach to determining the order of a finite state Markov chain whose transition probabilities are themselves governed by a homogeneous finite state Markov chain.  ...  The sequence was generated from a hidden Markov model with r = 2 hidden states and a q = 1 order Markov dependence for a b = 4 state observed sequence.  ... 
doi:10.1155/2002/683164 fatcat:ts35esy2xbhejiihtiqeaufiyi

The BUDS Language for Distributed Bayesian Machine Learning

Zekai J. Gao, Shangyu Luo, Luis L. Perez, Chris Jermaine
2017 Proceedings of the 2017 ACM International Conference on Management of Data - SIGMOD '17  
These are tightly coupled with the physical representation. In BUDS, these implementations are co-optimized along with the representation.  ...  -are simply logical abstractions useful for programming, and do not correspond to the actual implementation.  ...  For example, consider a Bayesian Hidden Markov Model for text (see Figure 5 in the Appendix).  ... 
doi:10.1145/3035918.3035937 dblp:conf/sigmod/GaoLPJ17 fatcat:if3w3wn6wvfwna4sbapvzei7qu

Dynamic Quantizer Design for Hidden Markov State Estimation Via Multiple Sensors With Fusion Center Feedback

M. Huang, S. Dey
2006 IEEE Transactions on Signal Processing  
Index Terms-Dynamic programming equation, dynamic quantization, hidden Markov models, sensor networks, state estimation. I.  ...  This paper considers the state estimation of hidden Markov models by sensor networks.  ...  measurements modeled by hidden Markov chains.  ... 
doi:10.1109/tsp.2006.874809 fatcat:uemetgskhfgsfl4my3n4clmol4

Page 2234 of Mathematical Reviews Vol. , Issue 86e [page]

1986 Mathematical Reviews  
A well-known important application is the detection of embedded or hidden networks in linear programming constraints.  ...  By exploiting the network structure, we are able to show that the iteration is globally convergent, monotonic, and (locally) quadratically con- vergent using only simple algebraic arguments.” 86e:90120  ... 

Learning Deep Structured Models [article]

Liang-Chieh Chen and Alexander G. Schwing and Alan L. Yuille and Raquel Urtasun
2015 arXiv   pre-print
Markov random fields (MRFs) are a great mathematical tool to encode such relationships.  ...  Towards this goal, we propose a training algorithm that is able to learn structured models jointly with deep features that form the MRF potentials.  ...  As expected, performance also grows with the number of hidden units.  ... 
arXiv:1407.2538v3 fatcat:2fzubi36mrcdrnba7lqljfbnwe

Matrix Distributed Processing and FermiQCD [article]

Massimo Di Pierro
2000 arXiv   pre-print
Here are few examples of FermiQCD Object Oriented capabilities (compared with examples in the standard textbook notation for Lattice QCD) 1) QCD: (algebra of Euclidean gamma matrices) A = γ µ γ 5 e 3iγ  ...  MPI calls are hidden inside the basic classes that constitute MDP and are invisible to the user.  ...  I also acknowledge I borrowed many Lattice QCD algorithms from existing CANOPY, MILC and UKQCD programs; I thank here the authors for letting me study their codes.  ... 
arXiv:hep-lat/0011083v1 fatcat:yqw2rt4c4fhgpnf2i2kat6mb4e

Estimating animal spirits: conservative risk calculation

Grzegorz Andruszkiewicz, Mark H. A. Davis, Sébastien Lleo
2014 Quantitative Finance Letters  
An enhanced Hidden Markov Model is used, for both the Shiller Home Price Index and a consumer confidence index.  ...  We conclude that both house prices and consumer confidence are driven by another hidden behavioural factor, interpreted as 'animal spirits'. Both data series imply similar paths of the hidden factor.  ...  We estimate parameters of a hidden Markov model with two hidden states in June 2006.  ... 
doi:10.1080/21649502.2014.946234 fatcat:lzxrd6csmrctlbz2upjb4pubiu
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