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Finding structure in time

J Elman
1990 Cognitive Science  
Finding Structure in Time JEFFREYL.ELMAN University of California, San Diego Time underlies many interesting human behaviors.  ...  In this simulation, the goal is to find the temporal structure of the XOR sequence.  ... 
doi:10.1016/0364-0213(90)90002-e fatcat:7cprhl5ysjdundsvptblq45abu

Finding Structure in Time

Jeffrey L. Elman
1990 Cognitive Science  
Time underlies many interesting human behaviors. Thus, the question of how to represent time in connectionist models is very important.  ...  One approach is to represent time implicitly by its effects on processing rather than explicitly (as in a spatial representation).  ...  In this simulation the goal was to find the temporal structure of the XOR sequence.  ... 
doi:10.1207/s15516709cog1402_1 fatcat:yj7y7ptixredxhtssld6sqlavm

Finding Structure in Time: Visualizing and Analyzing Behavioral Time Series

Tian Linger Xu, Kaya de Barbaro, Drew H. Abney, Ralf F. A. Cox
2020 Frontiers in Psychology  
time series.  ...  In this paper, we will introduce four techniques to interpret and analyze high-density multi-modal behavior data, namely, to: (1) visualize the raw time series, (2) describe the overall distributional  ...  Goldstein for their insights and comments on the topic of behavioral analysis in developmental science.  ... 
doi:10.3389/fpsyg.2020.01457 pmid:32793025 pmcid:PMC7393268 fatcat:rz5thuxjurbkrj7bddh4wdgdfq

Finding Kinematic Structure in Time Series Volume Data

Tomoyuki Mukasa, Shohei Nobuhara, Atsuto Maki, Takashi Matsuyama
2009 ELCVIA Electronic Letters on Computer Vision and Image Analysis  
Once we acquire a unique kinematic structure, we fit it to other Reeb graphs in the remaining frames, and describe the motion throughout the entire time series.  ...  This paper presents a new scheme for acquiring 3D kinematic structure and motion from time series volume data.  ...  Describe entire time series by the integrated kinematic structure. (1),(2),(3) are processes for acquiring a global shape structure. (4) is a process for finding intervals in which we can make correlations  ... 
doi:10.5565/rev/elcvia.164 fatcat:4y34ngqg2vb2nkdmavl7ifjjmu

Finding Common RNA Pseudoknot Structures in Polynomial Time [chapter]

Patricia A. Evans
2006 Lecture Notes in Computer Science  
This paper presents the first polynomial time algorithm for finding common RNA substructures that include pseudoknots and similar structures.  ...  While a more general problem is known to be NP-hard, this algorithm exploits special features of RNA structures to match RNA bonds correctly in polynomial time.  ...  Acknowledgements Much thanks are due to Kaizhong Zhang, whose concerns about the preliminary version of this paper, appearing in Combinatorial Pattern Matching 2006, enabled its improvement here.  ... 
doi:10.1007/11780441_21 fatcat:ht4czehxxvbqdmep7nkikloloa

Finding common RNA pseudoknot structures in polynomial time

Patricia A. Evans
2011 Journal of Discrete Algorithms  
This paper presents the first polynomial time algorithm for finding common RNA substructures that include pseudoknots and similar structures.  ...  While a more general problem is known to be NP-hard, this algorithm exploits special features of RNA structures to match RNA bonds correctly in polynomial time.  ...  Acknowledgements Much thanks are due to Kaizhong Zhang, whose concerns about the preliminary version of this paper, appearing in Combinatorial Pattern Matching 2006, enabled its improvement here.  ... 
doi:10.1016/j.jda.2011.04.002 fatcat:htjlfi4d6ffrdbp63hdlevoqka

Finding Algebraic Structure of Care in Time: A Deep Learning Approach [article]

Phuoc Nguyen, Truyen Tran, Svetha Venkatesh
2017 arXiv   pre-print
Existing methods are inadequate in capturing the dynamic structure of care. We propose an end-to-end model that reads medical record and predicts future risk.  ...  The model adopts the algebraic view in that discrete medical objects are embedded into continuous vectors lying in the same space.  ...  Acknowledgments The paper is partly supported by the Telstra-Deakin CoE in Big Data and Machine Learning.  ... 
arXiv:1711.07980v1 fatcat:fee33s6vtre55msuums4jfur3q

Finding Outliers in Linear and Nonlinear Time Series [chapter]

Pedro Galeano, Daniel Peña
2013 Robustness and Complex Data Structures  
There are two main alternatives to analyze and treat outliers in time series. First, robust procedures can be applied to obtain parameter estimates not affected by the presence of outliers.  ...  Outliers, or discordant observations, can have a strong effect on the model building process for a given time series.  ...  In this section, we briefly review the main findings in Tsay et al. (2000) and Galeano et al. (2006) .  ... 
doi:10.1007/978-3-642-35494-6_15 fatcat:326o4gghmvbhzbz2fdex7s6pmm

Finding Structural Similarity in Time Series Data Using Bag-of-Patterns Representation [chapter]

Jessica Lin, Yuan Li
2009 Lecture Notes in Computer Science  
As a result, many time series representations and distance measures have been proposed. However, most existing work on time series similarity search focuses on finding shape-based similarity.  ...  For long sequences, it is more appropriate to consider the similarity based on the higher-level structures.  ...  In this paper, we focus on finding structural similarities between time series data.  ... 
doi:10.1007/978-3-642-02279-1_33 fatcat:ljjgw3oaxnhhpofv5d7iywv3k4

Bypass strong V-structures and find an isomorphic labelled subgraph in linear time [chapter]

Heiko Dörr
1995 Lecture Notes in Computer Science  
This paper identifies a condition for which the existence of an isomorphic subgraph can be decided in linear time. The condition is evaluated in two steps.  ...  If this representation exists, the given algorithm constructively decides the subgraph isomorphism problem for the guest and the host graph in linear time.  ...  This fact will be observed in the next iteration. If we try to extend following the second alternative, we are lucky because we find a singular extension.  ... 
doi:10.1007/3-540-59071-4_57 fatcat:dlzjhxlqobgavnu2g237auuzne

Are apparent findings of nonlinearity due to structural instability in economic time series?

Gary Koop, Simon M. Potter
2001 Econometrics Journal  
time.  ...  An empirical exercise involving several macroeconomic time series shows that apparent¯ndings of threshold type nonlinearities could be due to structural instability.  ...  Such a model would have a linear structure at any point in time, but this structure will change in a way that is not predictable from the past history of the time series.  ... 
doi:10.1111/1368-423x.00055 fatcat:lpno45mqabfrrj4yycr6tqixny

Finding cycles and trees in sublinear time

Artur Czumaj, Oded Goldreich, Dana Ron, C. Seshadhri, Asaf Shapira, Christian Sohler
2012 Random structures & algorithms (Print)  
We present sublinear-time (randomized) algorithms for finding simple cycles of length at least k ≥ 3 and tree-minors in bounded-degree graphs.  ...  length in time O( √ N ), where N denotes the number of vertices.  ...  We next turn from finding cycles to finding tree-structures in graphs; that is, finding treeminors. Consider the following interesting special case.  ... 
doi:10.1002/rsa.20462 fatcat:zcl7kww23nh5lcnqn5bmuagmia

Are Apparent Findings of Nonlinearity Due to Structural Instability in Economic Time Series?

Gary Koop, Simon Potter
1999 Social Science Research Network  
time.  ...  An empirical exercise involving several macroeconomic time series shows that apparent¯ndings of threshold type nonlinearities could be due to structural instability.  ...  Such a model would have a linear structure at any point in time, but this structure will change in a way that is not predictable from the past history of the time series.  ... 
doi:10.2139/ssrn.163151 fatcat:qrywlh6ovvg4vasloepjczbcbe

An almost linear time algorithm for finding Hamilton cycles in sparse random graphs with minimum degree at least three

Alan Frieze, Simi Haber
2014 Random structures & algorithms (Print)  
If c is sufficiently large then our algorithm finds a Hamilton cycle in G δ≥3 n,m , m = cn, and runs in O(n 1+o(1) ) time and succeeds w.h.p. Remark 1.1.  ...  In Section 4 we discuss some "residual randomness" left over by 2greedy. In Section 5 we prove some structural properties of G δ≥3 n,m .  ...  Final Remarks We have shown that a Hamilton cycle can w.h.p. be found in O(n 1+o(1) )) time.  ... 
doi:10.1002/rsa.20542 fatcat:25dex4ayhfbddgfdwfuu6lp5ca

Structural Barriers to Timely Initiation of Antiretroviral Treatment in Vietnam: Findings from Six Outpatient Clinics

Dam Anh Tran, Anthony Shakeshaft, Anh Duc Ngo, John Rule, David P. Wilson, Lei Zhang, Christopher Doran, D. William Cameron
2012 PLoS ONE  
Structural barriers to timely ART initiation were poor linkage between HIV testing and HIV care and treatment services, lack of patient confidentiality and a shortage of HIV/AIDS specialists.  ...  The study was undertaken in six clinics from five provinces in Vietnam.  ...  In-depth interviews with patients were semi-structured and provided information on structural facilitators and barriers associated with timing of ART initiation and how these affect individual treatment  ... 
doi:10.1371/journal.pone.0051289 pmid:23240013 pmcid:PMC3519823 fatcat:sn4z2j7vdnh4tidatstctlqwa4
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