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Linear Additive Markov Processes
2017
Proceedings of the 26th International Conference on World Wide Web - WWW '17
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We introduce LAMP: the Linear Additive Markov Process. ...
Transitions in LAMP may be influenced by states visited in the distant history of the process, but unlike higher-order Markov processes, LAMP retains an efficient parameterization. ...
[`], the Generalized Linear Additive Markov Process glamp(w, P, f) evolves according to the following transition rule: Pr[Xt = xt | x0, . . . t i} , xt). ...
doi:10.1145/3038912.3052644
dblp:conf/www/0001RST17
fatcat:5gllvoqozrdapd5t4fqlevt3nm
Linear Additive Markov Processes
[article]
2017
arXiv
pre-print
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We introduce LAMP: the Linear Additive Markov Process. ...
Transitions in LAMP may be influenced by states visited in the distant history of the process, but unlike higher-order Markov processes, LAMP retains an efficient parametrization. ...
LAMP In this section we introduce the Linear Additive Markov Process (LAMP), and describe its properties.
Background Let [n] = {1, 2, . . . , n}. Let X be a state space of size n. ...
arXiv:1704.01255v1
fatcat:bgwvzqi2ijguhgwp266djewho4
Hitting probabilities in a Markov additive process with linear movements and upward jumps: Applications to risk and queueing processes
2004
The Annals of Applied Probability
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Motivated by a risk process with positive and negative premium rates, we consider a real-valued Markov additive process with finitely many background states. ...
It is known that the hitting probabilities of this additive process at lower levels have a matrix exponential form. ...
This dual process is obtained from the Markov additive process by time reversal and changing the sign of the additive component. ...
doi:10.1214/105051604000000206
fatcat:4eqjki7oeraupbh6dbs7qpl5a4
Generalized Linear Models, Generalized Additive Models and Neural Networks: Comparative Study in Medical Applications
[chapter]
2013
Advances in Regression, Survival Analysis, Extreme Values, Markov Processes and Other Statistical Applications
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The objective of this study is to compare the performance of generalized linear models (GLMs) with binary response ( McCullagh and Nelder, Generalized Linear Models. ...
Chapman and Hall, London, 1989), with the performance of generalized additive models (GAMs) with binary response (Hastie and Tibshirani, Generalized Additive Models. ...
process. ...
doi:10.1007/978-3-642-34904-1_33
fatcat:iv47ei3gejertlgfdjmdnmfsty
Page 770 of Mathematical Reviews Vol. , Issue 81B
[page]
1981
Mathematical Reviews
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Matheson [Management Sci. 18 (1971/72), 356-369; MR 45 # 1583] the results for additive Markov decision
Bh
Economics, operations research, programming, games ™
processes cannot be used directly. ...
The relations between the two formulations have been studied in the literature for Markov decision processes with an additive objective function and nice results have been achieved which can be used for ...
Page 2839 of Mathematical Reviews Vol. , Issue 2000d
[page]
2000
Mathematical Reviews
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The additive coalescent is the A-valued Markov process in which pairs of clusters of masses {x;,x;} merge into a cluster of mass x; + x; at rate x; + x,;. ...
P. (5-SYD-SM; Sydney); Law, J.S. (5-SYD; Sydney) Modelling random linear nucleation and growth by a Markov chain. (English summary)
J. Appl. Probab. 36 (1999), no. 1, 273-278. ...
Analysis of Discrete Markov Process by Probability Flow Graph
確率流れ線図による不連続マルコフ過程の解析
1967
Transactions of the Society of Instrument and Control Engineers
確率流れ線図による不連続マルコフ過程の解析
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A discrete stationary Markov process can be described by constant coefficient difference equations and analyzed conveniently by the z-transformation in the form of a generating function which reprensents ...
The author defines the probability flow graph for the Markov process distinguishing it from the conventional flow graphs.
Fig. 5 Cut of branch and addition of absorbing node ...
At first, the Markov process is represented in a signal flow graph. After that, the author presents a new concept in understanding the Markov process. ...
doi:10.9746/sicetr1965.3.26
fatcat:blnn2a3d65ag5li7pavfvnc4xe
A Kalman filter clock algorithm for use in the presence of flicker frequency modulation noise
2005
Metrologia
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The FFM is modelled approximately by a linear combination of Markov noise processes. Each Markov process is included in the Kalman filter and contributes an additional component to its state vector. ...
Both the validity of the model and the effectiveness of adding these additional components to the state vector are examined. ...
The FFM is modelled as a linear combination of Markov noise processes. Each Markov process is included in the Kalman filter and contributes an additional component to the state vector. ...
doi:10.1088/0026-1394/42/1/001
fatcat:hxgpqbfh4rbglmvdisfhuayysm
Page 1982 of Mathematical Reviews Vol. , Issue 2003C
[page]
2003
Mathematical Reviews
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Summary: “For an additive Markov process (Xn,Sn), n> 0, in which x, is a countable Markov chain, properties of compo- nents of factorization of the operator J — zA(s), where A(s) = (M{e-S! ...
(PL-SITU-IM; Gliwice) Properties of operators associated with Markov additive processes. Il. (Ukrainian. Ukrainian summary) Teor. Imovir. Mat. Stat. No. 57 (1997), 1-9; translation in Theory Probab. ...
An Efficient Computational Alternative to 'Using Linear Programming to Design Oil Pollution Detection Schedules'
1978
A I I E Transactions
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programming formulation for Markov decision processes. ...
Optimal schedules for patrol fligh ts of surveillance aircraft were found using linear programming. In this paper the model has been reformulated as a discre te time semi-Markov process. ...
doi:10.1080/05695557808975182
fatcat:zvz45moemfe2zl4mwyhn2mhdfq
Random perturbation methods with applications in Science and Engineering
2004
Computers and Mathematics with Applications
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Discrete-time stationary processes. 1.2. Discrete-time Markov processes. 1.3. Continuous-time stationary processes. 1.4. Continuous-time Markov processes. 2. ...
Discrete-time Markov processes. 2.3.3. Discrete-time stationary processes. 2.3.4. Continuous-time stationary processes. 2.4. Large deviation theorems. 2.4.1. Continuous-time Markov processes. 3. ...
doi:10.1016/s0898-1221(04)90109-5
fatcat:5x5skcf2ijfuvixp2vdakmhqsa
Linear Laws of Markov Chains with an Application for Anomaly Detection in Bitcoin Prices
[article]
2022
arXiv
pre-print
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Based on the results, linear laws typically became more complex (containing an additional third parameter that indicates hidden Markov property) in two periods: before the crash of cryptocurrency markets ...
To accomplish these goals, first, the linear laws of Markov chains are derived by using the time embedding of their (categorical) autocorrelation function. ...
law for Markov processes. ...
arXiv:2201.09790v1
fatcat:6b2e66iv4rbrnlmn25amoohshy
Semi-supervised Gaussian process latent variable model with pairwise constraints
2010
Neurocomputing
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(RBF + linear) kernel 1 st order Markov
(RBF + linear) kernel
1 st order Markov
Linear kernel
2 nd order Markov RBF kernel
[Wang et al, 2005]
25
Optimization
= inference of latent variables ...
[Bishop, 2006; Williams and Rasmussen, 1996]
9
Gaussian Process Regression
Mean of
predictive
distribution
Target
function
Sampled (x n , t n )
with additive noise
±2 std of
predictive ...
doi:10.1016/j.neucom.2010.01.021
fatcat:p7aelt5rtjeqfdfddy7sygcase
Comments Regarding `On the Identifiability of the Influence Model for Stochastic Spatiotemporal Spread Processes'
[article]
2018
arXiv
pre-print
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The identifiability analysis of a networked Markov chain model known as the influence model, as described in a recent contribution to Arxiv, is examined. ...
In addition, some concerns about the formulation of the identifiability problem and the proposed estimation approach are noted. ...
Introduction The influence model, which describes a class of networked discrete-state Markov chains with quasi-linear interactions [2, 3] , has proved useful for representing social processes in human ...
arXiv:1811.02171v1
fatcat:vps6ymjab5edfgnvl4vnncq4wq
Page 7042 of Mathematical Reviews Vol. , Issue 93m
[page]
1993
Mathematical Reviews
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Summary (translated from the Russian): “We consider a class of Markov decision processes (MDP) with additional constraints. ...
from Markov decision processes. ...
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