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3It's Not You, It's Me: The Impact of Choice Models and Ranking Strategies on Gender Imbalance in Music Recommendation
A. Ferraro, M. Ekstrand, and C. Bauer. Proceedings of the 18th ACM Conference on Recommender Systems, page 884–889. New York, NY, USA, Association for Computing Machinery, (Oct 8, 2024)
21 days ago by @bauerc
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fairness
myown
models
music
strategies
gender
bias
recsys
recommender
choice
fairnessmyownmodelsmusicstrategiesgenderbiasrecsysrecommenderchoice
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2Prescriptive Analytics: When Data- and Simulation-based Models Interact in a Cooperative Way
M. Affenzeller, M. Bögl, L. Fischer, F. Sobieczky, K. Yang, and J. Zenisek. 2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), page 1-8. (September 2022)
a year ago by @scch
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models
deep-learning
simulation
interact
cooperative
modelsdeep-learningsimulationinteractcooperative
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1The number of patients and events required to limit the risk of overestimation of intervention effects in meta-analysis--a simulation study.
K. Thorlund, G. Imberger, M. Walsh, R. Chu, C. Gluud, J. Wetterslev, G. Guyatt, P. Devereaux, and L. Thabane. PloS one, 6 (10): e25491 (January 2011)6400<m:linebreak></m:linebreak>JID: 101285081; 2011/02/24 received; 2011/09/06 accepted; 2011/10/18 epublish; ppublish;.
2 years ago by @jepcastel
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Meta-AnalysisasTopic
Theoretical
SampleSize
ResearchDesign
Humans
Risk
Probability
Models
Meta-AnalysisasTopicTheoreticalSampleSizeResearchDesignHumansRiskProbabilityModels
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1Assessing the performance of prediction models: a framework for traditional and novel measures.
E. Steyerberg, A. Vickers, N. Cook, T. Gerds, M. Gonen, N. Obuchowski, M. Pencina, and M. Kattan. Epidemiology (Cambridge, Mass.), 21 (1): 128-38 (January 2010)5495 JID: 9009644; ppublish; Models predictius.
2 years ago by @jepcastel
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ROCCurve
ReproducibilityofResults
Prognosis
RiskAssessment
EpidemiologicStudies
RiskAssessment:standards
Statistical
Models
RiskAssessment:methods
RiskAssessment:statistics&numericaldata
ROCCurveReproducibilityofResultsPrognosisRiskAssessmentEpidemiologicStudiesRiskAssessment:standardsStatisticalModelsRiskAssessment:methodsRiskAssessment:statistics&numericaldata
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1Meta-analysis and subgroups.
M. Borenstein, and J. Higgins. Prevention science : the official journal of the Society for Prevention Research, 14 (2): 134-43 (April 2013)7499<m:linebreak></m:linebreak>GR: DA019280/DA/NIDA NIH HHS/United States; GR: DA022799/DA/NIDA NIH HHS/United States; GR: DA025366/DA/NIDA NIH HHS/United States; GR: U105285807/Medical Research Council/United Kingdom; JID: 100894724; ppublish; Bona explicacií (i gràfics) de models fixes i aleatoris<m:linebreak></m:linebreak>Metaanàlisi; Anàlisi de subgrups.
2 years ago by @jepcastel
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Obesity
Theoretical
Humans
Statistical
Models
Morbid
Morbid:prevention&control
DataInterpretation
ObesityTheoreticalHumansStatisticalModelsMorbidMorbid:prevention&controlDataInterpretation
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2Statistical analysis of correlated data using generalized estimating equations: an orientation.
J. Hanley, A. Negassa, M. deB Edwardes, and J. Forrester. American journal of epidemiology, 157 (4): 364-75 (February 2003)5955<m:linebreak></m:linebreak>LR: 20071114; GR: 5P01/DK45734-05/DK/NIDDK NIH HHS/United States; GR: CA 70269/CA/NCI NIH HHS/United States; GR: R01 DA/KK11598-01/DA/NIDA NIH HHS/United States; JID: 7910653; CIN: Am J Epidemiol. 2003 Aug 1;158(3):289; author reply 289-90. PMID: 12882954; CIN: Am J Epidemiol. 2003 Aug 1;158(3):289; author reply 289-90. PMID: 12882953; ppublish;<m:linebreak></m:linebreak>Anàlisi de dades; GEE; Dades longitudinals.
2 years ago by @jepcastel
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SocioeconomicFactors
EpidemiologicMethods
Humans
BodyHeight
LongitudinalStudies
Statistical
Models
Child
SocioeconomicFactorsEpidemiologicMethodsHumansBodyHeightLongitudinalStudiesStatisticalModelsChild
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2What you see may not be what you get: a brief, nontechnical introduction to overfitting in regression-type models.
M. Babyak. Psychosomatic medicine, 66 (3): 411-21 (2004)15184705<m:linebreak></m:linebreak> <m:linebreak></m:linebreak>LR: 20071115; PUBM: Print; JID: 0376505; ppublish;<m:linebreak></m:linebreak> <m:linebreak></m:linebreak>Anàlisi de dades.
2 years ago by @jepcastel
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ResearchDesign
Humans
Psychophysiology:statistics&numericaldata
StatisticsasTopic:methods
PsychosomaticMedicine
DataInterpretation
ComputerSimulation
StatisticsasTopic:education
Statistical
Models
RegressionAnalysis
StatisticsasTopic
PsychosomaticMedicine:statistics&numericaldat
Psychophysiology
ResearchDesignHumansPsychophysiology:statistics&numericaldataStatisticsasTopic:methodsPsychosomaticMedicineDataInterpretationComputerSimulationStatisticsasTopic:educationStatisticalModelsRegressionAnalysisStatisticsasTopicPsychosomaticMedicine:statistics&numericaldatPsychophysiology
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1Novel metrics for evaluating improvement in discrimination: net reclassification and integrated discrimination improvement for normal variables and nested models.
M. Pencina, R. D'Agostino, and O. Demler. Statistics in medicine, 31 (2): 101-13 (January 2012)6488 CI: Copyright (c) 2011; JID: 8215016; aheadofprint; Models predictius; Proves diagnòstiques.
2 years ago by @jepcastel
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ROCCurve
RiskAssessment
CardiovascularDiseases:prevention&control
Humans
Male
Statistical
Models
EpidemiologicResearchDesign
RiskAssessment:methods
DiscriminantAnalysis
CardiovascularDiseases
ROCCurveRiskAssessmentCardiovascularDiseases:prevention&controlHumansMaleStatisticalModelsEpidemiologicResearchDesignRiskAssessment:methodsDiscriminantAnalysisCardiovascularDiseases
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1Performance measures for prediction models and markers: evaluation of predictions and classifications.
E. Steyerberg, B. Calster, and M. Pencina. Revista española de cardiología, 64 (9): 788-94 (September 2011)6490 CI: Copyright (c) 2011; JID: 0404277; 0 (Biological Markers); 0 (Cholesterol, HDL); 2011/04/25 received; 2011/04/26 accepted; 2011/07/16 aheadofprint; ppublish; Models predictius; Proves diagnòstiques; Introductori.
2 years ago by @jepcastel
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ROCCurve
Humans
Calibration
AreaUnderCurve
BiologicalMarkers
Forecasting
HeartDiseases:classification
DataInterpretation
Cholesterol
DecisionSupportTechniques
HDL
ProportionalHazardsModels
Cardiology:statistics&numericaldata
HDL:blood
Cardiology:methods
Statistical
Models
Forecasting:methods
HeartDiseases
Cardiology
ROCCurveHumansCalibrationAreaUnderCurveBiologicalMarkersForecastingHeartDiseases:classificationDataInterpretationCholesterolDecisionSupportTechniquesHDLProportionalHazardsModelsCardiology:statistics&numericaldataHDL:bloodCardiology:methodsStatisticalModelsForecasting:methodsHeartDiseasesCardiology
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1In search of fewer independent risk factors.
D. Brotman, E. Walker, M. Lauer, and R. O'Brien. Archives of internal medicine, 165 (2): 138-45 (January 2005)3841<m:linebreak></m:linebreak>Mesures d'associació.
2 years ago by @jepcastel
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CardiovascularDiseases:epidemiology
RCT
Humans
Male
AgeFactors
MultivariateAnalysis
PredictiveValueofTests
EpidemiologicMethods
RiskFactors
OddsRatio
Statistical
Models
ConfoundingFactors(Epidemiology)
CardiovascularDiseases:diagnosis
SensitivityandSpecificity
SexFactors
Female
CardiovascularDiseases
CardiovascularDiseases:epidemiologyRCTHumansMaleAgeFactorsMultivariateAnalysisPredictiveValueofTestsEpidemiologicMethodsRiskFactorsOddsRatioStatisticalModelsConfoundingFactors(Epidemiology)CardiovascularDiseases:diagnosisSensitivityandSpecificitySexFactorsFemaleCardiovascularDiseases
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1Logistic regression.
M. LaValley. Circulation, 117 (18): 2395-9 (May 2008)Regressió logística; Introductori; CV.
2 years ago by @jepcastel
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Animals
CardiovascularDiseases:epidemiology
SampleSize
Cardiovascular
Humans
Models
LogisticModels
CardiovascularDiseases:physiopathology
CardiovascularDiseases
AnimalsCardiovascularDiseases:epidemiologySampleSizeCardiovascularHumansModelsLogisticModelsCardiovascularDiseases:physiopathologyCardiovascularDiseases
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1Capability-based semantic interoperability of manufacturing resources: A BaSys 4.0 perspective
A. Perzylo, J. Grothoff, L. Lucio, M. Weser, S. Malakuti, P. Venet, V. Aravantinos, and T. Deppe. IFAC-PapersOnLine, 52 (13): 1590-1596 (2019)9th IFAC Conference on Manufacturing Modelling, Management and Control MIM 2019.
3 years ago by @porta
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based
models
modeling
units
modelling
systems
technologies
Intelligent
interoperability
assembly
manufacturing
ontology-based
knowledge
device
integration
basedmodelsmodelingunitsmodellingsystemstechnologiesIntelligentinteroperabilityassemblymanufacturingontology-basedknowledgedeviceintegration
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5Right for the Right Reasons: Training Differentiable Models by Constraining their Explanations
A. Ross, M. Hughes, and F. Doshi-Velez. Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, IJCAI-17, page 2662--2670. (2017)
4 years ago by @schwemmlein
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loss
models
lime
ai
function
explainable
lossmodelslimeaifunctionexplainable
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1A quantitative model of glucose signaling in yeast reveals an incoherent feed forward loop leading to a specific, transient pulse of transcription
S. Kuttykrishnan, J. Sabina, L. Langton, M. Johnston, and M. Brent. Proceedings of the National Academy of Sciences, 107 (38): 16743--16748 (Sep 21, 2010)
6 years ago by @karthikraman
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models
feed-forward
glucose-signalling
yeast
modelsfeed-forwardglucose-signallingyeast
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1Establishing an air pollution monitoring network for intra-urban population exposure assessment: A location-allocation approach
P. Kanaroglou, M. Jerrett, J. Morrison, B. Beckerman, M. Arain, N. Gilbert, and J. Brook. Atmospheric Environment, 39 (13): 2399 - 2409 (2005)12th International Symposium, Transport and Air Pollution.
7 years ago by @lautenschlager
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lursurvey
effects
Monitoring
assessment
models
Health
Traffic
Air
emissions
Location-allocation
networks
pollution
lursurveyeffectsMonitoringassessmentmodelsHealthTrafficAiremissionsLocation-allocationnetworkspollution
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1A physically-based model of the ionizing radiation from active galaxies for photoionization modeling
A. Thomas, B. Groves, R. Sutherland, M. Dopita, C. Jin, and L. Kewley. (2016)cite arxiv:1611.05165Comment: 14 pages, 9 figures, 1 table. Accepted for publication in ApJ.
8 years ago by @miki
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models
photoionisation
agn
modelsphotoionisationagn
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2DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification.
S. Lacoste-Julien, F. Sha, and M. Jordan. NIPS, page 897-904. Curran Associates, Inc., (2008)
10 years ago by @schwemmlein
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models
kallimachos
genreTM
topic
genre
lda
text
classification
modelskallimachosgenreTMtopicgenreldatextclassification
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1Conditionally Trained Latent Dirichlet Allocation for Text Modeling and Categorization
S. Lacoste-Julien, F. Sha, and M. Jordan. (2015)
10 years ago by @schwemmlein
show all tags
models
kallimachos
genreTM
topic
genre
lda
text
classification
modelskallimachosgenreTMtopicgenreldatextclassification
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1Protected interactive 3D graphics via remote rendering
D. University, M. University, M. University, I. Marco Tarini ISTI-CNR, I. Giuseppe Croccia ISTI-CNR, I. Paolo Cignoni ISTI-CNR, and I. Roberto Scopigno ISTI-CNR. Conference proceedings, (2004)
10 years ago by @sebares92
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3d
models
systems
management
rights
graphics
security
rendering
digital
remote
3dmodelssystemsmanagementrightsgraphicssecurityrenderingdigitalremote
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11Graphical Models, Exponential Families, and Variational Inference
M. Wainwright, and M. Jordan. Foundations and Trends in Machine Learning, 1 (1-2): 1-305 (2008)
11 years ago by @wittawatj
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models
graphical
modelsgraphical
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1Rule Interchange on the Web
H. Boley, M. Kifer, P. Pătrânjan, and A. Polleres. Reasoning Web, volume 4636 of Lecture Notes in Computer Science, Springer Berlin Heidelberg, (2007)
11 years ago by @robert.richter5
show all tags
adaptive
models
systems
web
user
adaptivemodelssystemswebuser
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2Markov chains models, algorithms and applications
W. Ching, and M. Ng. Springer, New York, (2006)
12 years ago by @telekoma
show all tags
models
ws1213
CTII:WS1213
algorithms
chains
book
master
uni
applications
markov
modelsws1213CTII:WS1213algorithmschainsbookmasteruniapplicationsmarkov
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1Untersuchung bestehender Geschäftsmodelle etablierter Cloud Anbieter
M. Gierczak, M. Söllner, and J. Leimeister. ConLife 2012 Academic Conference, Cologne, Germany, (2012)339.
13 years ago by @ls_leimeister
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Business
pub_jml
Cloud
Models
Computing
Geschäftsmodelle
pub_mgi
itegpub
pub_msö
Businesspub_jmlCloudModelsComputingGeschäftsmodellepub_mgiitegpubpub_msö
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1Three case studies in the Bayesian analysis of cognitive models
M. Lee. Psychonomic Bulletin & Review, (2008)
13 years ago by @sidyr
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bayesian
models
cognitive
bayesianmodelscognitive
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2Three generative, lexicalised models for statistical parsing
M. Collins. Proceedings of the eighth conference on European chapter of the Association for Computational Linguistics, page 16--23. Stroudsburg, PA, USA, Association for Computational Linguistics, (1997)
13 years ago by @jil
show all tags
wh
1997
models
lexicalized
docrped
parser
collins
movement
generative
wh1997modelslexicalizeddocrpedparsercollinsmovementgenerative
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1Formal Models and the Specification Process.
J. Bowen, and M. Hinchey. The Computer Science and Engineering Handbook, CRC Press, (1997)
13 years ago by @jpbowen
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formal
myown
models
process
software
methods
specification
engineering
formalmyownmodelsprocesssoftwaremethodsspecificationengineering
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4Expressing Business Process Models as OWL-S Ontologies
M. Aslam, S. Auer, J. Chen, and M. Hermann. Grid and Peer-to-Peer based Workflows (GPWW), September 4th, Vienna, Austria, volume 4103 of BPM 2006 Workshops, page 400-415. Berlin / Heidelberg, Springer, (September 2006)
14 years ago by @enitsirhc
show all tags
models
process
semantics
business
businessprocess
model
ontology
modelsprocesssemanticsbusinessbusinessprocessmodelontology
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1Applied linear regression models
J. Neter, W. Wasserman, and M. Kutner. Irwin, Burr Ridge, Ill. u.a., 2. ed. edition, (1989)
15 years ago by @d82becker
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models
linear
regression
modelslinearregression
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2Escalation and de-escalation of commitment to information systems projects: Insights from a project evaluation model
S. Pan, G. Pan, M. Newman, and D. Flynn. (2006)
15 years ago by @3gerp
show all tags
3gerp
models
ISP
evaluation
commitment
3gerpmodelsISPevaluationcommitment
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1Transfer of technology and knowledge – the story of an enterprise system implementation
A. Ahmad, and M. Newman. (2009)
15 years ago by @3gerp
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3gerp
models
transfer
erp
development
universities
IS
3gerpmodelstransfererpdevelopmentuniversitiesIS
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1Punctuated Process Modelling of Information Systems: An Illustration from a Mid-sized Enterprise
M. Newman, and S. Zhu. (2009)
15 years ago by @3gerp
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3gerp
models
processes
3gerpmodelsprocesses
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1Learning in graphical models
M. Jordan. (2003)
15 years ago by @folke
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models
graphical
learning
introduction
modelsgraphicallearningintroduction
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8An Introduction to Variational Methods for Graphical Models
M. Jordan, Z. Ghahramani, T. Jaakkola, and L. Saul. Mach. Learn., 37 (2): 183--233 (1999)
15 years ago by @folke
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variational
bayesian
models
graphical
variationalbayesianmodelsgraphical
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13Intelligent Agents: Theory and Practice
M. Wooldridge, and N. Jennings. (1995)
16 years ago by @skosta
show all tags
models
abm,
modelsabm,
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1Synoptic climatology of extreme fire-weather conditions across the southwest United States
M. Crimmins. International Journal of Climatology, 26 (8): 1001-1016 (2006)
16 years ago by @jgomezdans
show all tags
weathertype
models
fires
modeling
firemafs
wildfire
fire
synoptic
statistics
weathertypemodelsfiresmodelingfiremafswildfirefiresynopticstatistics
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1Multi-sensor model-data fusion for estimation of hydrologic and energy flux parameters
L. Renzullo, D. Barrett, A. Marks, M. Hill, J. Guerschman, Q. Mu, and S. Running. Remote Sensing of Environment, 112 (4): 1306--1319 (April 2008)
16 years ago by @jgomezdans
show all tags
models
inference
Bayes
vegetation
evapotranspiration
assimilation
remotesensing
uncertainty
moisture
drought
bayes
mcmc
Soil
satellite
evaporation
soilmoisture
statistics
modelsinferenceBayesvegetationevapotranspirationassimilationremotesensinguncertaintymoisturedroughtbayesmcmcSoilsatelliteevaporationsoilmoisturestatistics
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3Applying Vector Space Models to Ontology Link Type Suggestion
A. Weichselbraun, G. Wohlgenannt, A. Scharl, M. Granitzer, T. Neidhart, and A. Juffinger. Proc. 4th International Conference on Innovations in Information Technology Innovations '07, page 566--570. (2007)
16 years ago by @mgrani
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based
myown
models
(artificial
batch
system,
suggestion,
learning,
online
cosine
semantic
statistical
metric,
conference
nonhierarchical
relations,
learning
intelligence),
process,
link
space
systems,
type
design
similarity
analysis,
vector
knowledge
Web,
ontologies
ontology
basedmyownmodels(artificialbatchsystem,suggestion,learning,onlinecosinesemanticstatisticalmetric,conferencenonhierarchicalrelations,learningintelligence),process,linkspacesystems,typedesignsimilarityanalysis,vectorknowledgeWeb,ontologiesontology
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1Sensitivity of Constrained Linear Inversions to the Selection of the Lagrange Multiplier
M. King. Journal of the Atmospheric Sciences, 39 (6): 1356-1369 (June 1981)
16 years ago by @jgomezdans
show all tags
optical
models
inference
inversions
sensitivity
BRDF
constrained
remotesensing
brdf
uncertainty
opticalmodelsinferenceinversionssensitivityBRDFconstrainedremotesensingbrdfuncertainty
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1A haem cofactor is required for redox and light signalling by the AppA protein of Rhodobacter sphaeroides
Y. Han, M. Meyer, M. Keusgen, and G. Klug. Molecular microbiology, (May 2007)PMID: 17501930.
17 years ago by @mikromolbio
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Recombinant_Proteins
Coenzymes
Signal_Transduction
Molecular_Sequence_Data
Oxidation-Reduction
Tertiary
Spectrum_Analysis
Protein_Structure
Sequence_Deletion
Repressor_Proteins
Biological
Sequence_Alignment
Amino_Acid_Sequence
Hemin
Protein_Binding
Gene_Expression_Regulation
Models
Flavoproteins
Electrophoretic_Mobility_Shift_Assay
Escherichia_coli
Bacterial
DNA-Binding_Proteins
Rhodobacter_sphaeroides
Light
Heme
Bacterial_Proteins
IFZ
Recombinant_ProteinsCoenzymesSignal_TransductionMolecular_Sequence_DataOxidation-ReductionTertiarySpectrum_AnalysisProtein_StructureSequence_DeletionRepressor_ProteinsBiologicalSequence_AlignmentAmino_Acid_SequenceHeminProtein_BindingGene_Expression_RegulationModelsFlavoproteinsElectrophoretic_Mobility_Shift_AssayEscherichia_coliBacterialDNA-Binding_ProteinsRhodobacter_sphaeroidesLightHemeBacterial_ProteinsIFZ
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1On empirical exchange rate models: what does a rejection of the symmetry restriction on short-run interest rates mean?
M. Goldberg. Journal of International Money and Finance, 19 (5): 673--688 (October 2000)
17 years ago by @smicha
show all tags
models
Empirical
rate
exchange
modelsEmpiricalrateexchange
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1The term structure of interest rates in a sticky-price target zone model
B. Kempa, M. Nelles, and C. Pierdzioch. Journal of International Money and Finance, 18 (5): 817--834 (October 1999)
17 years ago by @smicha
show all tags
models
zone
sticky-price
target
modelszonesticky-pricetarget
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1The "price puzzle" reconsidered
M. Hanson. Journal of Monetary Economics, 51 (7): 1385--1413 (October 2004)
17 years ago by @smicha
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models
Structural
VAR
modelsStructuralVAR
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1Bootstrap prediction intervals for autoregressive time series
M. Clements, and J. Kim. Computational Statistics & Data Analysis, 51 (7): 3580--3594 (Apr 1, 2007)
17 years ago by @smicha
show all tags
models
Autoregressive
modelsAutoregressive
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1A GARCH model of the implied volatility of the Swiss market index from option prices
M. Sabbatini, and O. Linton. International Journal of Forecasting, 14 (2): 199--213 (Jun 1, 1998)
17 years ago by @smicha
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models
ARCH
modelsARCH
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1Solution of finite-horizon multivariate linear rational expectations models and sparse linear systems
M. Binder, and H. Pesaran. Journal of Economic Dynamics and Control, 24 (3): 325--346 (March 2000)
17 years ago by @smicha
show all tags
models
linear
expectations
Multivariate
rational
modelslinearexpectationsMultivariaterational
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1Supply potential and output gaps in West German manufacturing
M. Funke. International Journal of Forecasting, 13 (2): 211--222 (June 1997)
17 years ago by @smicha
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models
VAR
modelsVAR
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1Kalman filtering with truncated normal state variables for Bayesian estimation of macroeconomic models
M. Dueker. Economics Letters, 93 (1): 58--62 (October 2006)
17 years ago by @smicha
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models
Macroeconometric
modelsMacroeconometric
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1SUR estimation of multiple time-series models with heteroscedasticity and serial correlation of unknown form
M. Creel, and M. Farell. Economics Letters, 53 (3): 239--245 (December 1996)
17 years ago by @smicha
show all tags
models
time-series
Multiple
modelstime-seriesMultiple
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1Contemporaneous threshold autoregressive models: Estimation, testing and forecasting
M. Dueker, M. Sola, and F. Spagnolo. Journal of Econometrics, 141 (2): 517--547 (December 2007)
17 years ago by @smicha
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Nonlinear
models
Nonlinearmodels
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1Subsampling inference in threshold autoregressive models
J. Gonzalo, and M. Wolf. Journal of Econometrics, 127 (2): 201--224 (August 2005)
17 years ago by @smicha
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models
autoregressive
Threshold
modelsautoregressiveThreshold
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