Relevant bibliographies by topics / Latent variables model

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Latent variables model'

Author: Grafiati
Published: 4 June 2021
Last updated: 8 February 2022

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Journal articles on the topic "Latent variables model"

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Moustaki, Irini. "A Latent Variable Model for Ordinal Variables." Applied Psychological Measurement 24, no. 3 (2000): 211–23. http://dx.doi.org/10.1177/01466210022031679.

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Gates, Kathleen M., Zachary F. Fisher, and Kenneth A. Bollen. "Latent variable GIMME using model implied instrumental variables (MIIVs)." Psychological Methods 25, no. 2 (2020): 227–42. http://dx.doi.org/10.1037/met0000229.

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Barkalov, S. A., O. N. Bekirova, N. Yu Kalinina, and S. I. Moiseev. "Identification model based on latent variables." Journal of Physics: Conference Series 1679 (November 2020): 052029. http://dx.doi.org/10.1088/1742-6596/1679/5/052029.

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Wu, Changjing, Hongyu Zhao, Huaying Fang, and Minghua Deng. "Graphical model selection with latent variables." Electronic Journal of Statistics 11, no. 2 (2017): 3485–521. http://dx.doi.org/10.1214/17-ejs1331.

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Ogasawara, Haruhiko. "A Log-Bilinear Model with Latent Variables." Behaviormetrika 25, no. 2 (1998): 95–110. http://dx.doi.org/10.2333/bhmk.25.95.

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Pan, Deng, Kai Kang, Chunjie Wang, and Xinyuan Song. "Bayesian proportional hazards model with latent variables." Statistical Methods in Medical Research 28, no. 4 (2017): 986–1002. http://dx.doi.org/10.1177/0962280217740608.

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We consider a joint modeling approach that incorporates latent variables into a proportional hazards model to examine the observed and latent risk factors of the failure time of interest. An exploratory factor analysis model is used to characterize the latent risk factors through multiple observed variables. In commonly used confirmatory factor analysis, the number of latent variables and their observed indicators are specified prior to analysis. By contrast, the exploratory factor analysis model allows such information to be fully determined by the data. A Bayesian approach coupled with effic
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Harring, Jeffrey R. "A Spline Regression Model for Latent Variables." Educational and Psychological Measurement 74, no. 2 (2013): 197–213. http://dx.doi.org/10.1177/0013164413504295.

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Almuzara, Martín, Dante Amengual, and Enrique Sentana. "Normality tests for latent variables." Quantitative Economics 10, no. 3 (2019): 981–1017. http://dx.doi.org/10.3982/qe859.

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We exploit the rationale behind the Expectation Maximization algorithm to derive simple to implement and interpret LM normality tests for the innovations of the latent variables in linear state space models against generalized hyperbolic alternatives, including symmetric and asymmetric Student ts. We decompose our tests into third and fourth moment components, and obtain one‐sided likelihood ratio analogues, whose asymptotic distribution we provide. When we apply our tests to a common trend model which combines the expenditure and income versions of US aggregate real output to improve its meas
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Thielemann, Désirée, Marie-Ann Sengewald, Gregor Kappler, and Rolf Steyer. "A Probit Latent State IRT Model With Latent Item-Effect Variables." European Journal of Psychological Assessment 33, no. 4 (2017): 271–84. http://dx.doi.org/10.1027/1015-5759/a000417.

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Abstract. We present a probit latent state model for dichotomous items with one latent state variable for each occasion of measurement and one latent item-effect variable for each item, except for a reference item. All latent variables are well defined in terms of conditional probabilities. The model offers the possibility to include explanatory variables for the latent states as well as for the latent item-effect variables. We illustrate the model by a data example with the life satisfaction scale of the Freiburg Personality Inventory (FPI-R; Fahrenberg, Hampel, & Selg, 1984 ) assessed at
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Moustaki, Irini. "A latent trait and a latent class model for mixed observed variables." British Journal of Mathematical and Statistical Psychology 49, no. 2 (1996): 313–34. http://dx.doi.org/10.1111/j.2044-8317.1996.tb01091.x.

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Dissertations / Theses on the topic "Latent variables model"

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Katsikatsou, Myrsini. "Composite Likelihood Estimation for Latent Variable Models with Ordinal and Continuous, or Ranking Variables." Doctoral thesis, Uppsala universitet, Statistiska institutionen, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-188342.

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The estimation of latent variable models with ordinal and continuous, or ranking variables is the research focus of this thesis. The existing estimation methods are discussed and a composite likelihood approach is developed. The main advantages of the new method are its low computational complexity which remains unchanged regardless of the model size, and that it yields an asymptotically unbiased, consistent, and normally distributed estimator. The thesis consists of four papers. The first one investigates the two main formulations of the unrestricted Thurstonian model for ranking data along w
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Strader, Scott C. "A causal model examining AIDS prejudice : AIDS attitudes and homophobia as latent variables." Virtual Press, 1994. http://liblink.bsu.edu/uhtbin/catkey/917830.

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Prejudice and discrimination against people infected with Acquired Immune Deficiency Syndrome (AIDS) is widespread. A significant body of research has examined what personality and demographic characteristics appear to be related to discriminatory behavior, in an attempt to suggest who might be more likely to express prejudicial attitudes and discrimination against people with AIDS. This study tested two causal models which attempted to verify existing theories explaining the influences of demographic and attitudinal factors on the evaluation of a person with AIDS. Specifically, these models s
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Plassmann, Vandana Shah. "Ethnicity and Clothing Expenditures of U.S. Households: A Structural Equations Model with Latent Quality Variables." Diss., Virginia Tech, 2000. http://hdl.handle.net/10919/29221.

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The main objective of this study was to determine the relationship between household characteristics and the expenditure shares allocated among various categories of women's clothing for U.S. households belonging to different ethnic groups. The study also estimated unobserved latent quality variables based on household characteristics, and examined the effects of the latent quality variables on the expenditure shares for the various apparel categories. A Multiple Indicator-Multiple Cause Model, which is a special case of the general Structural Equations Model, was used to estimate separate Eng
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Dean, Nema. "Variable selection and other extensions of the mixture model clustering framework /." Thesis, Connect to this title online; UW restricted, 2006. http://hdl.handle.net/1773/8943.

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Phonphitakchai, Thanawat. "Modelling the usage rate of a DRT service : a discrete choice model with latent variables." Thesis, University of Aberdeen, 2011. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=165208.

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Demand Responsive Transport (DRT) is a relatively new form of public transport provision; it is an intermediate form somewhere between conventional bus and taxi services. Over the last decade, DRT services have grown in popularity mainly influenced by the development of transport telematics. The telematics-based DRT system, which forms the focus of this research, allows new generation DRT services to have greater flexibility in time and route design, and to enable immediate advance booking and response to travel requests. These DRT services have shown important advantages and benefits in sever
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Almeida, José Pedro Abreu. "The fitting of the German yield curve: a dynamic approach using latent, macroeconomic and stock market variables." Master's thesis, NSBE - UNL, 2010. http://hdl.handle.net/10362/10351.

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics<br>The purpose of this Work Project is to build a yield curve model for the German Government yield curve containing latent variables (Level, Slope and Curvature), macroeconomic variables (German IFO and Inflation Rate) and a stock market variable (German Stock Index DAX), while studying the yield curve dynamics. The model incorporates the Nelson and Siegel (1987) factor model under a State-Space framework and the estimation results provided a goo
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Koch, Rainer, Ulrich Julius, Werner Jaross, and Hans-Egbert Schröder. "Estimation of the Heritability of Latent Variables Which Are Included in a Structural Model for Metabolic Syndrome." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-137470.

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In a study looking for risk factors of atherosclerosis in families with combined hyperlipidemia and hypertension, clinical and biochemical data of 1,149 persons were analyzed to develop two hypothetical multivariate scores concerning the degree to which a patient is affected by the metabolic syndrome. The scores are based on a structural model for low-density cholesterol (LDL) and high-density cholesterol (HDL), triglycerides, uric acid, creatinine, glucose, insulin, systolic blood pressure and waist-to-hip ratio. Age, gender and body mass index were used for adjusting all variables. In segreg
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Koch, Rainer, Ulrich Julius, Werner Jaross, and Hans-Egbert Schröder. "Estimation of the Heritability of Latent Variables Which Are Included in a Structural Model for Metabolic Syndrome." Karger, 2001. https://tud.qucosa.de/id/qucosa%3A27735.

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In a study looking for risk factors of atherosclerosis in families with combined hyperlipidemia and hypertension, clinical and biochemical data of 1,149 persons were analyzed to develop two hypothetical multivariate scores concerning the degree to which a patient is affected by the metabolic syndrome. The scores are based on a structural model for low-density cholesterol (LDL) and high-density cholesterol (HDL), triglycerides, uric acid, creatinine, glucose, insulin, systolic blood pressure and waist-to-hip ratio. Age, gender and body mass index were used for adjusting all variables. In segreg
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Villegas, Arriola Claudia Miluska Maria Luisa, and Bazán Marjorie Daysi Huamán. "Satisfacción e inseguridad laboral como variables explicativas de la intención de renunciar al trabajo en jóvenes." Bachelor's thesis, Universidad Peruana de Ciencias Aplicadas (UPC), 2020. http://hdl.handle.net/10757/652967.

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El presente estudio tiene como objetivo determinar si las variables satisfacción e inseguridad laboral explican la intención de renunciar al trabajo en jóvenes. Se evaluó a 150 jóvenes de edades entre 20 a 35 años que trabajan en una empresa del rubro de telecomunicaciones. Se aplicó la Escala de Intenciones de Renunciar al Trabajo, Escala de Inseguridad Laboral y, por último, el Índice Breve de Satisfacción Laboral Afectiva, los cuales fueron validados en el contexto peruano. Finalmente, se obtuvo como resultado, mediante el Modelo Explicativo Latente, que la Satisfacción Laboral y la Insegur
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Frot, Benjamin. "Graphical model selection for Gaussian conditional random fields in the presence of latent variables : theory and application to genetics." Thesis, University of Oxford, 2016. https://ora.ox.ac.uk/objects/uuid:0a6799ed-fca1-48b2-89cd-ad6f2c0439af.

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The task of performing graphical model selection arises in many applications in science and engineering. The field of application of interest in this thesis relates to the needs of datasets that include genetic and multivariate phenotypic data. There are several factors that make this problem particularly challenging: some of the relevant variables might not be observed, high-dimensionality might cause identifiability issues and, finally, it might be preferable to learn the model over a subset of the collection while conditioning on the rest of the variables, e.g. genetic variants. We suggest
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Books on the topic "Latent variables model"

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Heinen, Ton. Discrete latent variable models. Tilburg University Press, 1993.

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Loglinear models with latent variables. Sage, 1993.

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Hagenaars, Jacques. Loglinear models with Latent Variables. SAGE Publications, Inc., 1993. http://dx.doi.org/10.4135/9781412984850.

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Semialgebraic statistics and latent tree models. CRC Press, Taylor & Francis Group, 2016.

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Dunson, David B., ed. Random Effect and Latent Variable Model Selection. Springer New York, 2008. http://dx.doi.org/10.1007/978-0-387-76721-5.

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Bartholomew, David, Martin Knott, and Irini Moustaki. Latent Variable Models and Factor Analysis. John Wiley & Sons, Ltd, 2011. http://dx.doi.org/10.1002/9781119970583.

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Bartholomew, David J. Latent variable models and factor analysis. 2nd ed. Arnold, 1999.

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Bartholomew, David J. Latent variable models and factor analysis. C. Griffin, 1987.

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1965-, Curran Patrick J., ed. Latent curve models: A structural equation perspective. John Wiley & Sons, 2005.

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Bollen, Kenneth A. Latent curve models: A structural equation perspective. Wiley Interscience, 2005.

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Book chapters on the topic "Latent variables model"

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Bartholomew, David J. "A General Latent Variable Model." In Unobserved Variables. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39912-1_5.

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Pierini, Andrea, and Antonello Maruotti. "A Multivariate Stochastic Volatility Model for Portfolio Risk Estimation." In Advances in Latent Variables. Springer International Publishing, 2014. http://dx.doi.org/10.1007/10104_2014_17.

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Sagan, Adam, and Barbara Pawełek. "Single-Indicator SEM with Measurement Error: Case of Klein I Model." In Advances in Latent Variables. Springer International Publishing, 2014. http://dx.doi.org/10.1007/10104_2014_25.

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Ongaro, Andrea, and Sonia Migliorati. "A Dirichlet Mixture Model for Compositions Allowing for Dependence on the Size." In Advances in Latent Variables. Springer International Publishing, 2014. http://dx.doi.org/10.1007/10104_2014_13.

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Wasserman, Theodore, and Lori Drucker Wasserman. "Latent Variables in the Diagnosis of Anxiety." In Therapy and the Neural Network Model. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-26921-0_11.

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Bollen, Kenneth A., and Catherine Zimmer. "An Overview of the Autoregressive Latent Trajectory (ALT) Model." In Longitudinal Research with Latent Variables. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-11760-2_5.

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Zanella, Angelo, Giuseppe Boari, Andrea Bonanomi, and Gabriele Cantaluppi. "A Simplified Latent Variable Structural Equation Model with Observable Variables Assessed on Ordinal Scales." In Statistical Models for Data Analysis. Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00032-9_43.

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Morlini, Isabella. "Using Latent Variables in Model Based Clustering: An E-Government Application." In Recent Developments in Modeling and Applications in Statistics. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-32419-2_1.

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Mavromatis, Panayotis. "HMM Analysis of Musical Structure: Identification of Latent Variables Through Topology-Sensitive Model Selection." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02394-1_19.

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Abdul Aziz Bin Husainan, Lamia, Hanan Ali AL-Shehri, and Muna Al-Razgan. "Investigating Arab DHH Usage of YouTube Videos Using Latent Variables in an Acceptance Technology Model." In Social Computing and Social Media. Human Behavior. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58559-8_1.

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Conference papers on the topic "Latent variables model"

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Kirillov, Alexander, Mikhail Gavrikov, Ekaterina Lobacheva, Anton Osokin, and Dmitry Vetrov. "Deep Part-Based Generative Shape Model with Latent Variables." In British Machine Vision Conference 2016. British Machine Vision Association, 2016. http://dx.doi.org/10.5244/c.30.88.

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Rafi, Selwa, Marc Castella, and Wojciech Pieczynski. "An extension of the ICA model using latent variables." In ICASSP 2011 - 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2011. http://dx.doi.org/10.1109/icassp.2011.5947157.

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Puignau, Sara Ahetze, Floridea Di Ciommo, and Sergi Saurí. "Latent variables definition for a new mobility model in Barcelona." In CIT2016. Congreso de Ingeniería del Transporte. Universitat Politècnica València, 2016. http://dx.doi.org/10.4995/cit2016.2016.2146.

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Based on the recent travel behaviour literature, time and space perceptions and the awareness of shared economy seem to gain importance in mobility patterns. The objective of this article is to evaluate how far the behaviour of new generations brings about different mobility patterns in Barcelona. For this purpose, we have designed a web-based survey that provides innovative revealed-preference data.DOI: http://dx.doi.org/10.4995/CIT2016.2016.2146
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Mazaheri, Amir, Boqing Gong, and Mubarak Shah. "Learning a Multi-concept Video Retrieval Model with Multiple Latent Variables." In 2016 IEEE International Symposium on Multimedia (ISM). IEEE, 2016. http://dx.doi.org/10.1109/ism.2016.0132.

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Han, Tian, Jiawen Wu, and Ying Nian Wu. "Replicating Active Appearance Model by Generator Network." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/305.

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A recent Cell paper [Chang and Tsao, 2017] reports an interesting discovery. For the face stimuli generated by a pre-trained active appearance model (AAM), the responses of neurons in the areas of the primate brain that are responsible for face recognition exhibit strong linear relationship with the shape variables and appearance variables of the AAM that generates the face stimuli. In this paper, we show that this behavior can be replicated by a deep generative model called the generator network, which assumes that the observed signals are generated by latent random variables via a top-down c
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Giesen, Joachim, Paul Kahlmeyer, Sören Laue, et al. "Method of Moments for Topic Models with Mixed Discrete and Continuous Features." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/333.

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Topic models are characterized by a latent class variable that represents the different topics. Traditionally, their observable variables are modeled as discrete variables like, for instance, in the prototypical latent Dirichlet allocation (LDA) topic model. In LDA, words in text documents are encoded by discrete count vectors with respect to some dictionary. The classical approach for learning topic models optimizes a likelihood function that is non-concave due to the presence of the latent variable. Hence, this approach mostly boils down to using search heuristics like the EM algorithm for p
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Cai, Ruichu, Zijian Li, Pengfei Wei, Jie Qiao, Kun Zhang, and Zhifeng Hao. "Learning Disentangled Semantic Representation for Domain Adaptation." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/285.

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Domain adaptation is an important but challenging task. Most of the existing domain adaptation methods struggle to extract the domain-invariant representation on the feature space with entangling domain information and semantic information. Different from previous efforts on the entangled feature space, we aim to extract the domain invariant semantic information in the latent disentangled semantic representation (DSR) of the data. In DSR, we assume the data generation process is controlled by two independent sets of variables, i.e., the semantic latent variables and the domain latent variables
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Yang, Shijie, Liang Li, Shuhui Wang, Weigang Zhang, Qingming Huang, and Qi Tian. "A Structured Latent Variable Recurrent Network With Stochastic Attention For Generating Weibo Comments." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/548.

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Building intelligent agents to generate realistic Weibo comments is challenging. For such realistic Weibo comments, the key criterion is improving diversity while maintaining coherency. Considering that the variability of linguistic comments arises from multi-level sources, including both discourse-level properties and word-level selections, we improve the comment diversity by leveraging such inherent hierarchy. In this paper, we propose a structured latent variable recurrent network, which exploits the hierarchical-structured latent variables with stochastic attention to model the variations
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Wang, Liwei, Siyu Tao, Ping Zhu, and Wei Chen. "Data-Driven Multiscale Topology Optimization Using Multi-Response Latent Variable Gaussian Process." In ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/detc2020-22595.

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Abstract The data-driven approach is emerging as a promising method for the topological design of the multiscale structure with greater efficiency. However, existing data-driven methods mostly focus on a single class of unit cells without considering multiple classes to accommodate spatially varying desired properties. The key challenge is the lack of inherent ordering or “distance” measure between different classes of unit cells in meeting a range of properties. To overcome this hurdle, we extend the newly developed latent-variable Gaussian process (LVGP) to creating multi-response LVGP (MRLV
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Zhao, Wentian, Shaojie Wang, Zhihuai Xie, Jing Shi, and Chenliang Xu. "GAN-EM: GAN Based EM Learning Framework." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/612.

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Expectation maximization (EM) algorithm is to find maximum likelihood solution for models having latent variables. A typical example is Gaussian Mixture Model (GMM) which requires Gaussian assumption, however, natural images are highly non-Gaussian so that GMM cannot be applied to perform image clustering task on pixel space. To overcome such limitation, we propose a GAN based EM learning framework that can maximize the likelihood of images and estimate the latent variables. We call this model GAN-EM, which is a framework for image clustering, semi-supervised classification and dimensionality
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Reports on the topic "Latent variables model"

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Gertler, Paul. A Latent Variable Model of Quality Determination. National Bureau of Economic Research, 1985. http://dx.doi.org/10.3386/w1750.

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Mislevy, Robert J., and Kathleen M. Sheehan. The Information Matrix in Latent-Variable Models. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada196609.

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Anandkumar, Anima, Rong Ge, Daniel Hsu, Sham M. Kakade, and Matus Telgarsky. Tensor Decompositions for Learning Latent Variable Models. Defense Technical Information Center, 2012. http://dx.doi.org/10.21236/ada604494.

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Collins, David H. Jr. Latent Variable Models for Quantification of Margins and Uncertainties. Office of Scientific and Technical Information (OSTI), 2013. http://dx.doi.org/10.2172/1088891.

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Hu, Yingyao. Microeconomic models with latent variables: applications of measurement error models in empirical industrial organization and labor economics. IFS, 2015. http://dx.doi.org/10.1920/wp.cem.2015.0315.

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Edwards, Susan L., Marcus E. Berzofsky, and Paul P. Biemer. Addressing Nonresponse for Categorical Data Items Using Full Information Maximum Likelihood with Latent GOLD 5.0. RTI Press, 2018. http://dx.doi.org/10.3768/rtipress.2018.mr.0038.1809.

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Full information maximum likelihood (FIML) is an important approach to compensating for nonresponse in data analysis. Unfortunately, only a few software packages implement FIML and even fewer have the capability to compensate for missing not at random (MNAR) nonresponse. One of these packages is Statistical Innovations’ Latent GOLD; however, the user documentation for Latent GOLD provides no mention of this capability. The purpose of this paper is to provide guidance for fitting MNAR FIML models for categorical data items using the Latent GOLD 5.0 software. By way of comparison, we also provid
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Harris, Jeffrey, and Sandra Sosa-Rubi. Impact of "Seguro Popular" on Prenatal Visits in Mexico, 2002-2005: Latent Class Model of Count Data with a Discrete Endogenous Variable. National Bureau of Economic Research, 2009. http://dx.doi.org/10.3386/w14995.

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Martínez, André, Fadel Ugarte, and Joaquín Zentner. Desigualdad de género en la participación laboral y remuneraciones en el grupo de países CID. Inter-American Development Bank, 2021. http://dx.doi.org/10.18235/0003179.

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La desigualdad en la participación laboral de las mujeres y su menor remuneración relativa, en comparación con los hombres, representa una de las principales fuentes de inequidad de género observada en los países de América Latina, y de los países del grupo CID en particular. Si bien es cierto, las brechas en participación laboral femenina se han reducido en las últimas tres décadas, dicha reducción ha sido apenas de 7 puntos porcentuales a nivel mundial, por lo que se vuelve necesario analizar cuáles son los factores que afectan la participación laboral femenina en la región para diseñar polí
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Freiría, Heber, Alejandro Nin Pratt, and Gonzalo Muñoz. Productividad y eficiencia en la producción ganadera pastoril en América Latina: Los casos de Bolivia y Colombia. Inter-American Development Bank, 2021. http://dx.doi.org/10.18235/0003150.

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El estudio examina el desempeño de la producción ganadera en Bolivia y Colombia. Se trata de dos ganaderías con diferente trayectoria, madurez tecnológica, y desempeño productivo, y que tienen en común la existencia de “frontera agrícola”, es decir, cambios de uso del suelo que permiten incorporar tierras de pastoreo a la ganadería, a partir de bosques. En el caso de Bolivia, el estudio se limitó a la región oriental, compuesta por los departamentos de Beni y Santa Cruz, que concentra la mayor parte del inventario ganadero del país. Beni, el departamento tradicionalmente ganadero, muestra esta
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10

Over, Thomas, Riki Saito, Andrea Veilleux, et al. Estimation of Peak Discharge Quantiles for Selected Annual Exceedance Probabilities in Northeastern Illinois. Illinois Center for Transportation, 2016. http://dx.doi.org/10.36501/0197-9191/16-014.

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This report provides two sets of equations for estimating peak discharge quantiles at annual exceedance probabilities (AEPs) of 0.50, 0.20, 0.10, 0.04, 0.02, 0.01, 0.005, and 0.002 (recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively) for watersheds in Illinois based on annual maximum peak discharge data from 117 watersheds in and near northeastern Illinois. One set of equations was developed through a temporal analysis with a two-step least squares-quantile regression technique that measures the average effect of changes in the urbanization of the watersheds used i
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