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Consistency of Feature Markov Processes

Peter Sunehag, Marcus Hutter
2010 arXiv   pre-print
We want a method that is asymptotically consistent in the sense it will provably eventually only choose between alternatives that satisfy an optimality property related to the used criterion.  ...  We extend our work to the case where there is side information that one can take advantage of and, furthermore, we briefly discuss the active setting where an agent takes actions to achieve desirable outcomes  ...  Definition 16 (Feature Markov Process, ΦMP) Suppose that P r(y n |Φ 0 (y 1 ), ..., Φ 0 (y 1:n )) = P r(y n |Φ 0 (y 1:n )) and that the state sequence is Markov, i.e.  ... 
arXiv:1007.2075v1 fatcat:53wb7vlv7nctlf4okccgj527qy

Consistency of Feature Markov Processes [chapter]

Peter Sunehag, Marcus Hutter
2010 Lecture Notes in Computer Science  
We want a method that is asymptotically consistent in the sense it will provably eventually only choose between alternatives that satisfy an optimality property related to the used criterion.  ...  We extend our work to the case where there is side information that one can take advantage of and, furthermore, we briefly discuss the active setting where an agent takes actions to achieve desirable outcomes  ...  Definition 16 (Feature Markov Process, ΦMP) Suppose that P r(y n |Φ 0 (y 1 ), ..., Φ 0 (y 1:n )) = P r(y n |Φ 0 (y 1:n )) and that the state sequence is Markov, i.e.  ... 
doi:10.1007/978-3-642-16108-7_29 fatcat:eydla6o4f5gdhhhs4xhrcu7cfu

Quaternion Markov Splicing Detection for Color Images Based on Quaternion Discrete Cosine Transform

2020 KSII Transactions on Internet and Information Systems  
Secondly, the proposed quaternion Markov features consist of global and local quaternion Markov, which utilize both magnitude and three phases to extract Markov features by using two different ways.  ...  Firstly, the proposed quaternion Markov features are extracted in QDCT domain.  ...  A novel quaternion Markov is proposed to extract classification features in QDCT domain, which consists of global quaternion Markov and local quaternion Markov.  ... 
doi:10.3837/tiis.2020.07.014 fatcat:pkcucwr4fvctrlyoxsalyjm7mu

Conditional Probability Based Steganalysis for JPEG Steganography

Ainuddin Wahid Wahab, Johann A. Briffa, Hans Georg Schaathun, Anthony T.S. Ho
2009 2009 International Conference on Signal Processing Systems  
In our experiment, we prove that the proposed technique works as well or better than the Markov process based technique in terms of classification accuracy on F5.  ...  This paper includes the introduction to conditional probability features, how the experiment works, and the discussion of the results.  ...  Our results also consistent with what published in [13] for Markov process based steganalysis.  ... 
doi:10.1109/icsps.2009.71 fatcat:hc4c7eh7sfhytbsbpuwwnigd3a

Fingerprint Recognition Using Markov Chain and Kernel Smoothing Technique with Generalized Regression Neural Network and Adaptive Resonance Theory with Mapping

Hemad Heidari Jobaneh
2019 Machine Learning Research  
Plus, two approaches are proposed with the intention of extracting statistical features predicated upon Kernel and Markov chain.  ...  In fact, two sets of features are extracted from both horizontal and vertical Markov chain, derived from the ridges angle around the aforementioned lines.  ...  To commence the process, two steps should be performed, consisting of the orientation of ridges and enhancement [19] .  ... 
doi:10.11648/j.mlr.20190401.12 fatcat:s5tujyoi4fbqrbeqjmrtvc4nu4

Gesture Recognition of Dance using Chain Code and Hidden Markov Model

Joko Sutopo, Universitas Teknologi Yogyakarta, Sleman, Indonesia
2019 International Journal of Advanced Trends in Computer Science and Engineering  
Dance one culture consists of motion.  ...  The novelty in this paper use Chain Code 15 (CC-15) to conduct the introduction featuring Dance with HMM classification, which produced an accuracy of 90% of ten (10) test data movement.  ...  ACKNOWLEDGEMENT The author would like to thank the Biocore Laboratory of the Faculty of Information and Communication Technology (FTMK), Universiti Teknikal Malaysia Melaka for the support of its facilities  ... 
doi:10.30534/ijatcse/2019/85862019 fatcat:tgv3zhzbqzfhnm2yqllhss6ah4

A Comprehensive Study on Third Order Statistical Features for Image Splicing Detection [chapter]

Xudong Zhao, Shilin Wang, Shenghong Li, Jianhua Li
2012 Lecture Notes in Computer Science  
We also test the robustness of third order statistical features, despite higher dimensionality, third order statistical features demonstrate the same robustness as that of second order features.  ...  Since the dimensionality exponentially depends on the order, dimensionality of the third order features is much larger than that of second order features, principal component analysis (PCA) is therefore  ...  Shi et al. in [9] proposed a natural image model for image splicing detection, the statistical features consists of moments of characteristic functions of wavelet sub-bands and first order Markov transition  ... 
doi:10.1007/978-3-642-32205-1_20 fatcat:vydcy7fyu5cqrif276bfzye3g4

Development of a Conversation State Prediction System [article]

Sujay Uday Rittikar
2021 arXiv   pre-print
In this study, the Markov Chains are used to identify and update the Speaker States for the next conversations between the same set of speakers, to enable identification of their states in the most natural  ...  With the evolution of the concept of Speaker diarization using LSTM, it is relatively easier to understand the speaker identities for specific segments of input audio stream data than manually tagging  ...  The Markov Chains are based on the idea of a stochastic process and Markov property.  ... 
arXiv:2107.01462v4 fatcat:377avhecarhkhagrjekf2nybpq

Predicting Metal-Binding Sites of Protein Residues

Serkan Küçükbay, Hasan Oğul
2015 Position Papers of the 2015 Federated Conference on Computer Science and Information Systems  
Metal ions in protein are critical to the function, structure and stability of protein. For this reason accurate prediction of metal binding sites in protein is very important.  ...  Several feature sets are employed to evaluate impact on prediction results.  ...  INTRODUCTION Protein plays a crucial role in all biological processes. And they consist of one or more long chains of amino acid residues.  ... 
doi:10.15439/2015f391 dblp:conf/fedcsis/KucukbayO15 fatcat:qlc6ldzmwrg2nlpysbjdo27ysu

Combinatorial optimization EDA using hidden Markov models

Marc-André Gardner, Christian Gagné, Marc Parizeau
2013 Proceeding of the fifteenth annual conference companion on Genetic and evolutionary computation conference companion - GECCO '13 Companion  
The Hidden Markov Model (HMM) is a well-known graphical model useful for modelling populations of variable-length sequences of discrete values.  ...  Estimation of Distribution Algorithms (EDAs) have been successfully applied to a wide variety of problems.  ...  Acknowledgements This work has been made possible through funding from NSERC (Canada) and access to computational resources of Calcul Québec / Compute Canada.  ... 
doi:10.1145/2464576.2482748 dblp:conf/gecco/GardnerGP13a fatcat:jlhor36y2ra47nyzsjh53mmbbe

Statistical modeling of daily rainfall occurrences

James A. Smith
1987 Water Resources Research  
The model, which is termed a Markov Bernoulli process, can be viewed as a sequence of Bernoulli trials with randomized success probabilities.  ...  Contained within the family of Markov Bernoulli models are Markov chain and Bernoulli trial models.  ...  This research was carried out at the Centre for Mathematics and Computer Science in Amsterdam with the support of a Fullbright postdoctoral research grant.  ... 
doi:10.1029/wr023i005p00885 fatcat:dtptyu7fi5hprdknom55abkzq4

Illumination-Invariant Face Identification Using Edge-Based Feature Vectors In Pseudo-2D Hidden Markov Models

Tadashi Shibata, Yasufumi Suzuki
2006 Zenodo  
Publication in the conference proceedings of EUSIPCO, Florence, Italy, 2006  ...  The authors would like to thank Takeshi Kanamori of The University of Tokyo for his contribution in carrying out the computer simulation.  ...  The model consists of six super states each of which contains an one-dimension Hidden Markov Model with six embedded states.  ... 
doi:10.5281/zenodo.53285 fatcat:a7pzqujryvg5hehaolhdhdqwji

Page 48 of Technometrics Vol. 2, Issue 1 [page]

1960 Technometrics  
If we want repair as a feature of our model, stationarity is essential to avoid extremely complicated analyses.  ...  Recall a Markov process is a stochastic process such that, given the system is in state EZ; at time & , no additional information concerning states of the system at previous times can alter the (conditional  ... 

Analysis of the axial stability for an assembly of optical modes with stochastic fluctuations type Markov chain

P Martinez Vara, C Gutierrez Ojeda, A Garcia Guzman, E Saldivia Gomez, G Arenas Muñoz, JC Atenco Cuautle, G Martinez Niconoff
2020 Annals of Mathematics and Physics  
Each subinterval is linked to a Bessel mode of integer order selected according to a Markov-chain-type process.  ...  These stochastic processes are associated with a sequence of time subintervals of duration ∆T.  ...  A fundamental point consists in the analysis of the stability of the process.  ... 
doi:10.17352/amp.000012 fatcat:kqohzmyfszecljn52od34jwjty

Georegistration of airborne hyperspectral image data

C. Lee, J. Bethel
2001 IEEE Transactions on Geoscience and Remote Sensing  
A suite of geometric sensor and platform modeling tools has been developed which have achieved consistent subpixel accuracy in orthorectification experiments.  ...  The most important contributors to the subpixel rectification accuracy have been the first order Gauss-Markov model with control linear features.  ...  In this approach, the state vector consists of six EO parameters for the first order Gauss-Markov model.  ... 
doi:10.1109/36.934067 fatcat:ae3sc7f4cbendfjxheloihpina
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