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Tree-Structured Conditional Random Fields for Semantic Annotation [chapter]

Jie Tang, Mingcai Hong, Juanzi Li, Bangyong Liang
2006 Lecture Notes in Computer Science  
This paper is concerned with semantic annotation on hierarchically dependent data (hierarchical semantic annotation).  ...  We propose a Tree-structured Conditional Random Field (TCRF) model to better incorporate dependencies across the hierarchically laid-out information.  ...  This model provides a novel way of incorporating the dependencies across the hierarchical structure to improve the performance of hierarchical semantic annotation.  ... 
doi:10.1007/11926078_46 fatcat:ibpjb2vki5bjflcw7l6ujgcsyu

Is Early Vision Optimized for Extracting Higher-order Dependencies?

Yan Karklin, Michael S. Lewicki
2005 Neural Information Processing Systems  
Our work unifies several related approaches and observations about natural image structure and suggests that hierarchical models might yield better representations of image structure throughout the hierarchy  ...  Linear implementations of the efficient coding hypothesis, such as independent component analysis (ICA) and sparse coding models, have provided functional explanations for properties of simple cells in  ...  of the data L = log P (x|A) over the data ensemble, thereby learning a compact, efficient representation of structure in natural images.  ... 
dblp:conf/nips/KarklinL05 fatcat:363bjjcjtzcy5kre6d76mln23a

Segregating the core computational faculty of human language from working memory

M. Makuuchi, J. Bahlmann, A. Anwander, A. D. Friederici
2009 Proceedings of the National Academy of Sciences of the United States of America  
Functional imaging data revealed that the processes for structure and memory operate separately but co-operatively in the left inferior frontal gyrus; activities in the LPO increased as a function of structural  ...  In contrast to simple structures in animal vocal behavior, hierarchical structures such as center-embedded sentences manifest the core computational faculty of human language.  ...  We thank Josefine Sporer for help in constructing the stimulus material, Jonas Obleser for help with fMRI data analyses, Timm Wetzel for providing the DWI datasets, Enrico Kaden for preprocessing of the  ... 
doi:10.1073/pnas.0810928106 pmid:19416819 pmcid:PMC2688876 fatcat:npgj5ak4f5ephizblwkcfqke34


Felipe Schneider Costa, Maria Marlene De Souza Pires, Silvia Modesto Nassar
2013 Journal of Computer Science  
However, depending on the scenario utilized (network structure, number of samples or training cases, number of variables), the network may not provide appropriate results.  ...  This study uses a process variable selection, using the chi-squared test to verify the existence of dependence between variables in the data model in order to identify the reasons which prevent a Bayesian  ...  Fig. 1 . 1 Graphic structure of a naïve Bayesian network Fig. 2 . 2 Graphic structure of a hierarchical Bayesian network (with intermediate nodes) • Receiving the training data set as input • Calculating  ... 
doi:10.3844/jcssp.2013.1487.1495 fatcat:y4yermertrhwpgjqoqjb6c6o7a

A Time-Dependent Hierarchical Model for Elastic and Inelastic Scattering Data Analysis of Aerogels and Similar Soft Materials

Cedric J. Gommes
2022 Gels  
The data, however, come in the form of space- and time-correlation functions, and models are required to convert them into time-dependent structures.  ...  We present here a general time-dependent stochastic model of hierarchical structures, with scale-invariant fractals as a particular case, which enables one to jointly analyze elastic and inelastic scattering  ...  manuscript and suggesting the one-sentence proof of Equation (28) .  ... 
doi:10.3390/gels8040236 pmid:35448137 pmcid:PMC9025713 fatcat:3argfkvk4zg7zcvd5vw57ketfi

Value at Risk of portfolios using copulas

Kiwoong Byun, Seongjoo Song
2021 Communications for Statistical Applications and Methods  
This paper compares copulas such as elliptical, vine, and hierarchical copulas in computing the VaR of portfolios to find appropriate copula functions in various dependence structures among asset return  ...  In the simulation studies under various dependence structures and real data analysis, the hierarchical Clayton copula shows the best performance in the VaR calculation using four assets.  ...  The hierarchical Clayton copula was the best in prediction (out-of-sample performance) in both simulation studies and real data applications, regardless of the dependence structure of the underlying distribution  ... 
doi:10.29220/csam.2021.28.1.059 fatcat:sffr5fxwobdnbgdvhzaf7ufpde

Persistence of hierarchical network organization and emergent topologies in models of functional connectivity [article]

Ali Safari, Paolo Moretti, Ibai Diez, Jesus M. Cortes, Miguel Ángel Muñoz
2021 arXiv   pre-print
Functional networks provide a topological description of activity patterns in the brain, as they stem from the propagation of neural activity on the underlying anatomical or structural network of synaptic  ...  In this computational study, we introduce a novel methodology to monitor the persistence and breakdown of hierarchical order in functional networks, generated from computational models of activity spreading  ...  Let us remark that the idea of analyzing the dependence of s 1 on θ in functional networks is not new, but it was developed byGallos and Figure 1 : 1 Persistence and breakdown of hierarchical organization  ... 
arXiv:2003.04741v3 fatcat:zvsnef3f5ngrrki2vrgvmwa6ym

Hierarchical artificial grammar processing engages Broca's area

Jörg Bahlmann, Ricarda I. Schubotz, Angela D. Friederici
2008 NeuroImage  
These results indicate that Broca's area is part of a neural circuit that is responsible for the processing of hierarchical structures in an artificial grammar.  ...  When comparing the processing of hierarchical dependencies to adjacent dependencies, significantly higher activations were observed in Broca's area and the adjacent rim of the ventral premotor cortex (  ...  Behavioral data indicated that participants conducted slightly more errors in the hierarchically structured trials (5% errors) in comparison to the adjacent dependency rule (2% errors).  ... 
doi:10.1016/j.neuroimage.2008.04.249 pmid:18554927 fatcat:4dg7dugnnffa5kup75eslnt2ei

Main aspects of system hierarchy in ecological landscape research

Andrzej Richling, Jerzy Lechnio
2013 Miscellanea Geographica: Regional Studies on Development  
This requires the development of landscape schemes in the form of hierarchical structural and functional systems.  ...  The definition of these concepts and their characteristics are crucial for the ability to describe a landscape system, in terms of its structural and functional composition and valuation, as well as assessment  ...  This requires the development of landscape schemes in the form of hierarchical structural and functional systems .  ... 
doi:10.2478/v10288-012-0049-7 fatcat:rbilttiehncftkdzsfg6uy3to4

HA-SLA: A Hierarchical Autonomic SLA Model for SLA Monitoring in Cloud Computing

Ahmad Mosallanejad, Rodziah Atan
2013 Journal of Software Engineering and Applications  
It is proposed in this model that each SLA has connection with dependent SLAs in different layers of cloud computing, hierarchically, whereby each SLA should be able to monitor its attributes on its own  ...  In this paper, a model is proposed as hierarchical autonomic (HA)-SLA based on cloud computing nature.  ...  The HA-SLA builds an effective hierarchical connection between dependent SLAs in different layers of cloud computing consisting of IaaS, PaaS and SaaS as illustrated in Figure 1 .  ... 
doi:10.4236/jsea.2013.63b025 fatcat:bdrrm2siyjdxjl4f2fic74h2z4

Conquering hierarchical difficulty by explicit chunking

Tian-Li Yu, David E. Goldberg
2006 Proceedings of the 8th annual conference on Genetic and evolutionary computation - GECCO '06  
Pelikan and Goldberg [14] proposed a scalable hierarchical problem called the hierarchical trap (hTrap). hTrap is composed of three major components (Figure 1 ): 1. Structure.  ...  The hierarchical trap structure is a balanced k-ary tree.  ...  Air Force Office of Scientific Research, or the U.S.  ... 
doi:10.1145/1143997.1144210 dblp:conf/gecco/YuG06 fatcat:kymhm5aqtrd5bpvagsfwuuuvka

Academic conference homepage understanding using constrained hierarchical conditional random fields

Xin Xin, Juanzi Li, Jie Tang, Qiong Luo
2008 Proceeding of the 17th ACM conference on Information and knowledge mining - CIKM '08  
Different from traditional information extraction tasks, the data in academic conference homepages has complex structural dependencies across multiple Web pages.  ...  This problem consists of three labeling tasks -labeling conference function pages, function blocks, and attributes.  ...  In this task, structure and label dependences information are helpful. The LP 2 algorithm, however, can not use structure information as features and can not take advantages of label dependences.  ... 
doi:10.1145/1458082.1458254 dblp:conf/cikm/XinLTL08 fatcat:7mg26ndp7vgl7pymyu3u33dvri

The hierarchical system of distributed objects work control

Dariusz Bober
2009 Annales UMCS Informatica  
The structure of GS is usually an up-down depended hierarchy where the processes of their inter work control are implemented as two sides (up-down, down-up) information exchange.  ...  In this way, the layer of data interchange of GS subcomponents will migrate to the next/new level of abstraction.  ...  hierarchical structure of their work control and/or management.  ... 
doi:10.2478/v10065-009-0007-y fatcat:z5bulml3yvcjjgym3ijl4bosiq

Hierarchical Structure in Sequence Processing: How to Measure It and Determine Its Neural Implementation

Julia Uddén, Mauricio Jesus Dias Martins, Willem Zuidema, W. Tecumseh Fitch
2019 Topics in Cognitive Science  
In many domains of human cognition, hierarchically structured representations are thought to play a key role.  ...  In this paper, we start with some foundational definitions of key phenomena like "sequence" and "hierarchy," and then outline potential signatures of hierarchical structure that can be observed in behavioral  ...  Preparation of this paper was also supported by Austrian Science Fund (FWF) DK Grant "Cognition & Communication" (#W1262-B29) to WTF.  ... 
doi:10.1111/tops.12442 pmid:31364310 fatcat:xllqzhhkhrd4nlttgl7d6hhg4i

Compact data structure and scalable algorithms for the sparse grid technique

Alin Murarasu, Josef Weidendorfer, Gerrit Buse, Daniel Butnaru, Dirk Pflüger
2011 Proceedings of the 16th ACM symposium on Principles and practice of parallel programming - PPoPP '11  
The resulting data structure consumes a minimum amount of memory.  ...  In its original form, it relies heavily on recursion and complex data structures, thus being far from well-suited for GPUs.  ...  UK-C0020, made by King Abdullah University of Science and Technology (KAUST).  ... 
doi:10.1145/1941553.1941559 dblp:conf/ppopp/MurarasuWBBP11 fatcat:voszcfoqqjflxamcrzhz5byoee
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