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Computing Conditional Probabilities in Markovian Models Efficiently
[chapter]
2014
Lecture Notes in Computer Science
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For computing conditional probabilities or expected values under ω-regular conditions in Markov chains, we introduce a new transformation of Markov chains that incorporates the effect of the condition ...
Using adaptions of known automata-based methods, our algorithm can be generalized for computing the maximal conditional probabilities for ω-regular events under ω-regular conditions. ...
Conditional Probabilities in Markov Chains In what follows, let M = (S, P ) be a finite Markov chain as in Section 2 and ψ an ω-regular condition. ...
doi:10.1007/978-3-642-54862-8_43
fatcat:7sg5uq6u6jfqvo44df7qdfu5lu
LTL Model Checking of Interval Markov Chains
[chapter]
2013
Lecture Notes in Computer Science
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Interval Markov chains (IMCs) generalize ordinary Markov chains by having interval-valued transition probabilities. ...
We consider the problem of computing values for the unknown probabilities in an IMC that maximize the probability of satisfying an ω-regular specification. ...
Given an interval Markov chain M with set of states S and a labelling function V : S → Σ, we want to compute a Markov chain refining M that optimizes the probability of satisfying a given ω-regular property ...
doi:10.1007/978-3-642-36742-7_3
fatcat:l3mhblxf3nfgrc7tssc2idw6eu
Simulated Annealing
[chapter]
2010
International Series in Operations Research and Management Science
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The key feature of simulated annealing is that it provides a mechanism to escape local optima by allowing hill-climbing moves (i.e., moves which worsen the objective function value) in hopes of finding ...
Its ease of implementation and convergence properties and its use of hill-climbing moves to escape local optima have made it a popular technique over the past two decades. ...
Acknowledgments This work is supported in part by the Air Force Office of Scientific Research (FA9550-07-1-0232). The authors wish to thank the anonymous referees for their feedback on this chapter. ...
doi:10.1007/978-1-4419-1665-5_1
fatcat:idntn7ghpnc6div67wrwchizru
Adaptive Low-Nonnegative-Rank Approximation for State Aggregation of Markov Chains
[article]
2018
arXiv
pre-print
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Motivated by the success of the nuclear norm relaxation in low rank minimization problems, we propose an atomic regularizer as a convex surrogate for the nonnegative rank and formulate a convex optimization ...
Because the atomic regularizer itself is not computationally tractable, we instead solve a sequence of problems involving a nonnegative factorization of the Markov transition matrices by using the proximal ...
Therefore, we admit that the stochastic system satisfies Markov property, and approximate it by a finitestate Markov chain. ...
arXiv:1810.06032v1
fatcat:hsiw7zimjne65gdwm5lyk6eezm
Phase-type distributions in stochastic automata networks
2008
European Journal of Operational Research
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Stochastic Automata Networks (Sans) are high-level formalisms for modeling very large and complex Markov chains in a compact and structured manner. ...
In this paper we show how phase-type distributions may be incorporated into Sans thereby providing the wherewithal by which arbitrary distributions can be used which in turn leads to an improved ability ...
This is followed by a second step which completes the reduction of the original Ph-San to a regular San. The findings in this paper relate only to continuous-time Markov chains. ...
doi:10.1016/j.ejor.2007.02.019
fatcat:vvh3idav6zccbc36m2st6z2ove
Extrapolation Methods for fixed-point Multilinear PageRank computations
[article]
2019
arXiv
pre-print
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2019 pre-print arXiv:1906.01494v1 fatcat:5jyc4mz3rje7vetzl6smxt5wy4
In this work we consider a particular class of nonnegative tensors associated to the multilinear PageRank modification of higher-order Markov chains. ...
Based on the simplified topological ϵ-algorithm in its restarted form, we introduce an extrapolation-based acceleration of power method type algorithms, namely the shifted fixed-point method and the inner-outer ...
As for standard chains with memory of length 1, a higher-order Markov chain with a memory of length m − 1 can be represented by the m-order transition tensor p i1,i2... ...
arXiv:1906.01494v2
fatcat:egww5n3ldzaindwotuoamfkr7y
Multisource data fusion for bandlimited signals: a Bayesian perspective
2006
AIP Conference Proceedings
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We obtained promising results in reconstructing a super-resolved signal from two blurred and noisy shifted observations, using a Gaussian Markov chain as a prior. ...
The model resolution, the geometric distortions, the blur and the regularity of the sampling grid can be arbitrary for each sensor. The method is designed to handle realistic Gauss+Poisson noise. ...
For the sake of simplicity, we consider a first order Gaussian Markov Random Field (Markov chain if N =1) parametrized by a single smoothness parameter ω. ...
doi:10.1063/1.2423299
fatcat:rmwe6vbhmrgebhgmhjxxru7ojm
Online matrix factorization for Markovian data and applications to Network Dictionary Learning
[article]
2020
arXiv
pre-print
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2020 pre-print arXiv:1911.01931v4 fatcat:hozsqzatvndebjplqy4lu67dgqOther Versions
even when the data matrices are functions of some underlying Markov chain satisfying a mild mixing condition. ...
As the main application, by combining online non-negative matrix factorization and a recent MCMC algorithm for sampling motifs from networks, we propose a novel framework of Network Dictionary Learning ...
LB was supported by by the Institute for Advanced Study Charles Simonyi Endowment, ARO YIP award W911NF1910027, NSF CAREER award CCF-1845076, and AFOSR YIP award FA9550-19-1-0026. ...
arXiv:1911.01931v6
fatcat:wr262y3wpnc2vgm4r7esggfuau
A stochastic multiscale model for electricity generation capacity expansion
2014
European Journal of Operational Research
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We present an efficient method for coupling multiple temporal scales using the framework of singular perturbation theory for the control of Markov processes in continuous time. ...
We show that the uncertainties that exist in many energy planning problems, in particular load demand uncertainty and uncertainties in generation availability, can be captured with a multiscale model. ...
The transition probabilities were obtained by identifying the maximum likelihood Markov Chain of de-trended hourly load data. ...
doi:10.1016/j.ejor.2013.07.022
fatcat:bh3efbl4nbdv3j7fq7sznznyai
Are Lock-Free Concurrent Algorithms Practically Wait-Free?
[article]
2013
arXiv
pre-print
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2013 pre-print arXiv:1311.3200v1 fatcat:zebh4ujcwnbpbducp2azeklcsm
Our analysis relates the individual performance of processes with the global performance of the system using Markov chain lifting between a complex per-process chain and a simpler system progress chain ...
In other words, programmers can keep on designing simple lock-free algorithms instead of complex wait-free ones, and in practice, they will get wait-free progress. ...
Also, in this case, ℓ i ≥ √ n/c, by calculation. If the phase is regular, then the size of b i decreases by Ω( √ n), w.h.p. ...
arXiv:1311.3200v2
fatcat:ticwbey4djatpbbzz24flggybi
A comparison of techniques for on-line incremental learning of HMM parameters in anomaly detection
2009
2009 IEEE Symposium on Computational Intelligence for Security and Defense Applications
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Hidden Markov Models (HMMs) have been shown to provide a high level performance for detecting anomalies in intrusion detection systems. ...
When learning sequences with a finite length, on-line incremental versions of these algorithms can improve discrimination by allowing for convergence over several training iterations. ...
The training is then restarted, by re-initializing the models at random, and performing the batch algorithms using the accumulated blocks of data (Ω train 1 ∪ Ω train 2 ,Ω valid 1 ∪ Ω valid 2 ) , and so ...
doi:10.1109/cisda.2009.5356542
dblp:conf/cisda/KhreichGMS09
fatcat:pmu2gtfi3zctpnxv6xvtwfin5a
Proactive Dynamic Distributed Constraint Optimization Problems
2022
The Journal of Artificial Intelligence Research
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D-DCOPs solve a sequence of static problems by reacting to changes in the environment as the agents observe them. Such reactive approaches ignore knowledge about future changes of the problem. ...
To solve DCOPs in a dynamic environment, Dynamic DCOPs (D-DCOPs) have been proposed to model the inherent dynamism present in many coordination problems. ...
This research is partially supported by the United States-Israel Binational Science Foundation (BSF) under award 2018081, the United States National Science Foundation (NSF) under awards 1838364 and 2143706 ...
doi:10.1613/jair.1.13499
fatcat:77dxspow5vczffvjkktwgf2xyi
Are lock-free concurrent algorithms practically wait-free?
2014
Proceedings of the 46th Annual ACM Symposium on Theory of Computing - STOC '14
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Our analysis relates the individual performance of processes with the global performance of the system using Markov chain lifting between a complex per-process chain and a simpler system progress chain ...
Recently, Herlihy and Shavit [12] suggested that perhaps the answer lies in a surprising property of lock-free algorithms: in practice, they often behave as if they were wait-free (and similarly, deadlock-free ...
Also, in this case, ℓ i ≥ √ n/c, by calculation. If the phase is regular, then the size of b i decreases by Ω( √ n), w.h.p. ...
doi:10.1145/2591796.2591836
dblp:conf/stoc/AlistarhCS14
fatcat:hw74hdfn5vfdxczjag67mxvjmq
Are Lock-Free Concurrent Algorithms Practically Wait-Free?
2016
Journal of the ACM
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Our analysis relates the individual performance of processes with the global performance of the system using Markov chain lifting between a complex per-process chain and a simpler system progress chain ...
Recently, Herlihy and Shavit [12] suggested that perhaps the answer lies in a surprising property of lock-free algorithms: in practice, they often behave as if they were wait-free (and similarly, deadlock-free ...
Also, in this case, ℓ i ≥ √ n/c, by calculation. If the phase is regular, then the size of b i decreases by Ω( √ n), w.h.p. ...
doi:10.1145/2903136
fatcat:qvmowsapkbb6zkfqo5ilujnjpa
Stability and Experimental Comparison of Prototypical Iterative Schemes for Total Variation Regularized Problems
2016
Computational Methods in Applied Mathematics
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For a popular non-smooth minimization problem arising in image processing, we discuss the suitable application of three prototypical methods and their stability. ...
DFG via the priority program "Reliable Simulation Techniques in Solid Mechanics, Development of Non-standard Discretization Methods, Mechanical and Mathematical Analysis" (SPP 1748). ...
The authors acknowledge financial support for the project "Finite Element approximation of functions of bounded variation and application to model of damage, fracture and plasticity" (BA 2268/2-1) by the ...
doi:10.1515/cmam-2016-0014
fatcat:7t7ceouxrrf7jhk4j6rkrst2qq
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