Bibliografías temáticas / Exact and approximate inferences

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Literatura académica sobre el tema "Exact and approximate inferences"

Autor: Grafiati
Publicado: 25 de mayo de 2024
Última modificación: 27 de julio de 2025

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Artículos de revistas sobre el tema "Exact and approximate inferences"

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Wu, Lang. "Exact and Approximate Inferences for Nonlinear Mixed-Effects Models With Missing Covariates." Journal of the American Statistical Association 99, no. 467 (2004): 700–709. http://dx.doi.org/10.1198/016214504000001006.

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Mekhnacha, Kamel, Juan-Manuel Ahuactzin, Pierre Bessière, Emmanuel Mazer, and Linda Smail. "Exact and approximate inference in ProBT." Revue d'intelligence artificielle 21, no. 3 (2007): 295–332. http://dx.doi.org/10.3166/ria.21.295-332.

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Akagi, Yasunori, Takuya Nishimura, Yusuke Tanaka, Takeshi Kurashima, and Hiroyuki Toda. "Exact and Efficient Inference for Collective Flow Diffusion Model via Minimum Convex Cost Flow Algorithm." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (2020): 3163–70. http://dx.doi.org/10.1609/aaai.v34i04.5713.

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Collective Flow Diffusion Model (CFDM) is a general framework to find the hidden movements underlying aggregated population data. The key procedure in CFDM analysis is MAP inference of hidden variables. Unfortunately, existing approaches fail to offer exact MAP inferences, only approximate versions, and take a lot of computation time when applied to large scale problems. In this paper, we propose an exact and efficient method for MAP inference in CFDM. Our key idea is formulating the MAP inference problem as a combinatorial optimization problem called Minimum Convex Cost Flow Problem (C-MCFP)
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Abe, Takayuki, and Manabu Iwasaki. "EXACT AND APPROXIMATE INFERENCES FOR AN EXPONENTIAL MEAN FROM TYPE I CENSORED DATA." Bulletin of informatics and cybernetics 37 (December 2005): 31–39. http://dx.doi.org/10.5109/12589.

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YANG, HANN-PYI JAMES, and WEI-KEI SHIUE. "COMPARISON OF FAILURE INTENSITIES FROM TWO POISSON PROCESSES." International Journal of Reliability, Quality and Safety Engineering 02, no. 03 (1995): 235–43. http://dx.doi.org/10.1142/s0218539395000186.

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Statistical inferences for ratio and difference of intensities from two Poisson processes are reviewed. Both fixed time periods case and fixed number of failures case are considered. Exact results whenever available are described with emphasis on hypothesis testing procedures and confidence intervals construction. Some approximate confidence intervals are studied and simulation results indicate that these intervals are adequate even with small sample size.
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Karami, Md Jamil Hasan. "Assessing Goodness of Approximate Distributions for Inferences about Parameters in Nonlinear Regression Model." Dhaka University Journal of Science 71, no. 1 (2023): 13–16. http://dx.doi.org/10.3329/dujs.v71i1.65267.

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It is often crucial to make inferences about parameters of a nonlinear regression model due to a dependency of Fisher information on the parameter being estimated. Here, the distribution of the relevant test statistic is not exact, but approximate. Therefore, similar conclusion, based on the values of different test statistics, may not be reached. This study shows, in this circumstance, how to come up with a nonlinear regression model that can be used for forecasting and other related purposes. The goodness of the approximate distributions, F and χ 2 , has been assessed to reach a correct deci
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El-Sagheer, Rashad M., Taghreed M. Jawa, and Neveen Sayed-Ahmed. "Inferences for Generalized Pareto Distribution Based on Progressive First-Failure Censoring Scheme." Complexity 2021 (December 7, 2021): 1–11. http://dx.doi.org/10.1155/2021/9325928.

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In this article, we consider estimation of the parameters of a generalized Pareto distribution and some lifetime indices such as those relating to reliability and hazard rate functions when the failure data are progressive first-failure censored. Both classical and Bayesian techniques are obtained. In the Bayesian framework, the point estimations of unknown parameters under both symmetric and asymmetric loss functions are discussed, after having been estimated using the conjugate gamma and discrete priors for the shape and scale parameters, respectively. In addition, both exact and approximate
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Lintusaari, Jarno, Paul Blomstedt, Tuomas Sivula, Michael U. Gutmann, Samuel Kaski, and Jukka Corander. "Resolving outbreak dynamics using approximate Bayesian computation for stochastic birth-death models." Wellcome Open Research 4 (January 25, 2019): 14. http://dx.doi.org/10.12688/wellcomeopenres.15048.1.

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Earlier research has suggested that approximate Bayesian computation (ABC) makes it possible to fit simulator-based intractable birth-death models to investigate communicable disease outbreak dynamics with accuracy comparable to that of exact Bayesian methods. However, recent findings have indicated that key parameters such as the reproductive number R may remain poorly identifiable with these models. Here we show that the identifiability issue can be resolved by taking into account disease-specific characteristics of the transmission process in closer detail. Using tuberculosis (TB) in the Sa
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Lintusaari, Jarno, Paul Blomstedt, Brittany Rose, et al. "Resolving outbreak dynamics using approximate Bayesian computation for stochastic birth–death models." Wellcome Open Research 4 (August 30, 2019): 14. http://dx.doi.org/10.12688/wellcomeopenres.15048.2.

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Earlier research has suggested that approximate Bayesian computation (ABC) makes it possible to fit simulator-based intractable birth–death models to investigate communicable disease outbreak dynamics with accuracy comparable to that of exact Bayesian methods. However, recent findings have indicated that key parameters, such as the reproductive number R, may remain poorly identifiable with these models. Here we show that this identifiability issue can be resolved by taking into account disease-specific characteristics of the transmission process in closer detail. Using tuberculosis (TB) in the
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Kifle, Yehenew G., Alain M. Moluh, and Bimal K. Sinha. "Inference about a Common Mean Vector from Several Independent Multinormal Populations with Unequal and Unknown Dispersion Matrices." Mathematics 12, no. 17 (2024): 2723. http://dx.doi.org/10.3390/math12172723.

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This paper addresses the problem of making inferences about a common mean vector from several independent multivariate normal populations with unknown and unequal dispersion matrices. We propose an unbiased estimator of the common mean vector, along with its asymptotic estimated variance, which can be used to test hypotheses and construct confidence ellipsoids, both of which are valid for large samples. Additionally, we discuss an approximate method based on generalized p-values. The paper also presents exact test procedures and methods for constructing exact confidence sets for the common mea
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Tesis sobre el tema "Exact and approximate inferences"

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Ducamp, Gaspard. "PROCOP : probabilistic rules compilation and optimisation." Electronic Thesis or Diss., Sorbonne université, 2021. http://www.theses.fr/2021SORUS090.

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Adoptées depuis plus de 20 ans par le monde de l’industrie, les règles métiers (business rules) offrent la possibilité à des utilisateurs non-informaticiens de définir des politiques de prise de décision de manière simple et intuitive. Pour faciliter leurs utilisations, des systèmes à base de règles, dits « systèmes de gestion des règles métier », ont été développés, séparant la logique métier de l’application informatique. S’ils sont adaptés pour traiter des données structurées et complètes, ils ne permettent pas aisément de travailler sur des données probabilistes. PROCOP (Probabilistic Rule
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Tucker, Dewey S. (Dewey Stanton). "Stochastic realization theory for exact and approximate multiscale models." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/34468.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.<br>Includes bibliographical references (p. [245]-252).<br>The thesis provides a detailed analysis of the independence structure possessed by multiscale models and demonstrates that such an analysis provides important insight into the multiscale stochastic realization problem. Multiscale models constitute a broad class of probabilistic models which includes the well--known subclass of multiscale autoregressive (MAR) models. MAR models have proven useful in a variety of different a
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Cabo, Nodar Marta. "Exact and approximate algorithms for the inventory routing problem." Thesis, University of Southampton, 2003. https://eprints.soton.ac.uk/50599/.

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In this thesis we develop exact and approximate algorithms for the inventory routing problem (IRP). The inventory routing problem is one of deciding an optimal delivery policy for a set of customers through a given planning period. Customers can hold inventory and do not need deliveries every day. Deliveries are carried out by a fleet of homogeneous vehicles that must be routed to travel a minimum distance while visiting all customers scheduled for that day. Decisions concern which customers to be visited and how much to deliver to each of them must be taken. A new formulation for the IRP is p
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Ahern, Zeke Alexander. "Exact and approximate optimisation for strategic bus network planning." Thesis, Queensland University of Technology, 2020. https://eprints.qut.edu.au/206458/1/Zeke_Ahern_Thesis.pdf.

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This thesis contributes to the area of transportation network design at the strategic level, considering objectives for the passenger and operator. The main goal of the research is to improve the existing methods by developing new and more rigorous approaches to integrating route choice, service frequency and adequately accounting for passenger waiting time. An exact model was developed: providing a concise non-ambiguous description to the problem. Case study problem instances found that exact methods implemented by commercial solvers are not scalable for practical problems. Therefore, meta-he
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Markovsky, Ivan. "Exact and approximate modeling of linear systems : a behavioral approach /." Philadelphia, Pa. : Society for Industrial and Applied Mathematics, 2006. http://www.loc.gov/catdir/enhancements/fy0708/2005057537-d.html.

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Taylor, Michael. "Exact and approximate epidemic models on networks : theory and applications." Thesis, University of Sussex, 2013. http://sro.sussex.ac.uk/id/eprint/45258/.

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This thesis is concerned with modelling the spread of diseases amongst host populations and the epidemics that result from this process. We are primarily interested in how networks can be used to model the various heterogeneities observable in real-world populations. Firstly, we start with the full system of Kolmogorov/master equations for a simple Susceptible-Infected-Susceptible (SIS) type epidemic on an arbitrary contact network. From this general framework, we rigorously derive sets of ODEs that describe the exact dynamics of the expected number of individuals and pairs of individuals. We
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Igwe, Tobenna. "An empirical study on computation of exact and approximate equilibria." Thesis, University of Liverpool, 2018. http://livrepository.liverpool.ac.uk/3016935/.

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The computation of Nash equilibria is one of the central topics in game theory, which has received much attention from a theoretical point of view. Studies have shown that the problem of finding a Nash equilibrium is PPAD-complete, which implies that we are unlikely to find a polynomial-time algorithm for this problem. Naturally, this has led to a line of work studying the complexity of finding approximate Nash equilibria. This thesis examines the computation of such approximate Nash equilibria within several classes of games from an empirical perspective. In this thesis, we address the comput
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Diaz, Bobillo Ignacio Javier. "The general ℓ₁ optimal multiblock problem : exact and approximate solutions." Thesis, Massachusetts Institute of Technology, 1992. http://hdl.handle.net/1721.1/12798.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1992.<br>Includes bibliographical references (leaves 119-123).<br>by Ignacio Javier Diaz-Bobillo.<br>Ph.D.
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Hassan, Abdeljabbar Hassan Mohammed Albarra. "Parallel Scheduling in the Cloud Systems : Approximate and Exact Methods." Thesis, Université de Lorraine, 2016. http://www.theses.fr/2016LORR0223/document.

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Cette thèse porte sur la résolution exacte et heuristique de plusieurs problèmes ayant des applications dans le domaine de l'Informatique dématérialisé (cloud computing). L'Informatique dématérialisée est un domaine en plein extension qui consiste à mutualiser les machines/serveurs en définissant des machines virtuelles représentant des fractions des machines/serveurs. Il est nécessaire d'apporter des solutions algorithmiques performantes en termes de temps de calcul et de qualité des solutions. Dans cette thèse, nous nous sommes intéressés dans un premier temps au problème d'ordonnancement su
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Hassan, Abdeljabbar Hassan Mohammed Albarra. "Parallel Scheduling in the Cloud Systems : Approximate and Exact Methods." Electronic Thesis or Diss., Université de Lorraine, 2016. http://www.theses.fr/2016LORR0223.

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Cette thèse porte sur la résolution exacte et heuristique de plusieurs problèmes ayant des applications dans le domaine de l'Informatique dématérialisé (cloud computing). L'Informatique dématérialisée est un domaine en plein extension qui consiste à mutualiser les machines/serveurs en définissant des machines virtuelles représentant des fractions des machines/serveurs. Il est nécessaire d'apporter des solutions algorithmiques performantes en termes de temps de calcul et de qualité des solutions. Dans cette thèse, nous nous sommes intéressés dans un premier temps au problème d'ordonnancement su
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Libros sobre el tema "Exact and approximate inferences"

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Reinhard, Klette, ed. Euclidean shortest paths: Exact or approximate algorithms. Springer-Verlag, 2011.

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Chang, Yin-Wen. Exact and Approximate Methods for Machine Translation Decoding. [publisher not identified], 2015.

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Ivan, Markovsky, ed. Exact and approximate modeling of linear systems: A behavioral approach. Society for Industrial and Applied Mathematics, 2006.

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Kiss, Istvan Z. Mathematics of Epidemics on Networks: From Exact to Approximate Models. Springer International Publishing, 2017.

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Chen, Hsing-Ta. Delving Into Dissipative Quantum Dynamics: From Approximate to Numerically Exact Approaches. [publisher not identified], 2016.

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Glowinski, R. Exact and approximate controllability for distributed parameter systems: A numerical approach. Cambridge University Press, 2008.

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Constanda, Christian, Paul J. Harris, and Bardo E. J. Bodmann, eds. Exact and Approximate Solutions for Mathematical Models in Science and Engineering. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-59591-2.

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Hartley, T. T. Exact and approximate solutions to the oblique shock equations for real-time applications. University of Akron, Electrical Engineering Dept., 1991.

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Burstein, Joseph. Exact numerical solutions of nonlinear differential equations, short algorithms: After three centuries of approximate methods. Metrics Press, 2002.

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Klette, Reinhard, and Fajie Li. Euclidean Shortest Paths: Exact or Approximate Algorithms. Springer London, Limited, 2014.

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Capítulos de libros sobre el tema "Exact and approximate inferences"

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Kwatra, Saloni, and Vicenç Torra. "Empirical Evaluation of Synthetic Data Created by Generative Models via Attribute Inference Attack." In IFIP Advances in Information and Communication Technology. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-57978-3_18.

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AbstractThe disclosure risk of synthetic/artificial data is still being determined. Studies show that synthetic data generation techniques generate similar data to the original data and sometimes even the exact original data. Therefore, publishing synthetic datasets can endanger the privacy of users. In our work, we study the synthetic data generated from different synthetic data generation techniques, including the most recent diffusion models. We perform a disclosure risk assessment of synthetic datasets via an attribute inference attack, in which an attacker has access to a subset of public
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Azzolini, Damiano, Elena Bellodi, and Fabrizio Riguzzi. "Approximate Inference in Probabilistic Answer Set Programming for Statistical Probabilities." In AIxIA 2022 – Advances in Artificial Intelligence. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-27181-6_3.

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Abstract“Type 1” statements were introduced by Halpern in 1990 with the goal to represent statistical information about a domain of interest. These are of the form “x% of the elements share the same property”. The recently proposed language PASTA (Probabilistic Answer set programming for STAtistical probabilities) extends Probabilistic Logic Programs under the Distribution Semantics and allows the definition of this type of statements. To perform exact inference, PASTA programs are converted into probabilistic answer set programs under the Credal Semantics. However, this algorithm is infeasibl
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Muhamed, Aashiq, Sriram Srinivasan, Choon-Hui Teo, et al. "Web-Scale Semantic Product Search with Large Language Models." In Advances in Knowledge Discovery and Data Mining. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-33380-4_6.

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AbstractDense embedding-based semantic matching is widely used in e-commerce product search to address the shortcomings of lexical matching such as sensitivity to spelling variants. The recent advances in BERT-like language model encoders, have however, not found their way to realtime search due to the strict inference latency requirement imposed on e-commerce websites. While bi-encoder BERT architectures enable fast approximate nearest neighbor search, training them effectively on query-product data remains a challenge due to training instabilities and the persistent generalization gap with c
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Tsurkov, Vladimir. "Exact and Approximate Aggregation." In Large-scale Optimization — Problems and Methods. Springer US, 2001. http://dx.doi.org/10.1007/978-1-4757-3243-6_1.

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Cygan, Marek, and Marcin Pilipczuk. "Exact and Approximate Bandwidth." In Automata, Languages and Programming. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02927-1_26.

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Godbole, Anant P., Sanjay Khunger, and Esther Ososanya. "Exact and Approximate Hypercube Reliabilities." In Runs and Patterns in Probability. Springer US, 1994. http://dx.doi.org/10.1007/978-1-4613-3635-8_10.

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Helgaker, Trygve, Poul Jørgensen, and Jeppe Olsen. "Exact and Approximate Wave Functions." In Molecular Electronic-Structure Theory. John Wiley & Sons, Ltd, 2014. http://dx.doi.org/10.1002/9781119019572.ch4.

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Elad, Michael. "From Exact to Approximate Solutions." In Sparse and Redundant Representations. Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-7011-4_5.

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Alon, Noga, and Shai Gutner. "Balanced Hashing, Color Coding and Approximate Counting." In Parameterized and Exact Computation. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-11269-0_1.

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Dodson, M. M. "Abstract Exact and Approximate Sampling Theorems." In New Perspectives on Approximation and Sampling Theory. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08801-3_1.

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Actas de conferencias sobre el tema "Exact and approximate inferences"

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Naseri, Keihan, and Hadi Jahanirad. "A Runtime Reconfigurable Exact-Approximate Full-Adder Design." In 2024 6th Iranian International Conference on Microelectronics (IICM). IEEE, 2024. https://doi.org/10.1109/iicm65053.2024.10824335.

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Sandhya, Yenimireddy, and Arun Sekar Rajasekaran. "Performance Analysis of Exact/Approximate Multipliers for Image Processing Applications." In 2024 4th International Conference on Emerging Frontiers in Electrical and Electronic Technologies (ICEFEET). IEEE, 2024. https://doi.org/10.1109/icefeet64463.2024.10867204.

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Marinescu, Radu, Haifeng Qian, Alexander Gray, et al. "Approximate Inference in Logical Credal Networks." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/632.

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The Logical Credal Network or LCN is a recent probabilistic logic designed for effective aggregation and reasoning over multiple sources of imprecise knowledge. An LCN specifies a set of probability distributions over all interpretations of a set of logical formulas for which marginal and conditional probability bounds on their truth values are known. Inference in LCNs involves the exact solution of a non-convex non-linear program defined over an exponentially large number of non-negative real valued variables and, therefore, is limited to relatively small problems. In this paper, we present A
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van Bremen, Timothy, and Ondrej Kuzelka. "Approximate Weighted First-Order Model Counting: Exploiting Fast Approximate Model Counters and Symmetry." 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.2020/587.

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We study the symmetric weighted first-order model counting task and present ApproxWFOMC, a novel anytime method for efficiently bounding the weighted first-order model count of a sentence given an unweighted first-order model counting oracle. The algorithm has applications to inference in a variety of first-order probabilistic representations, such as Markov logic networks and probabilistic logic programs. Crucially for many applications, no assumptions are made on the form of the input sentence. Instead, the algorithm makes use of the symmetry inherent in the problem by imposing cardinality c
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Lee, K. David, Eric Wiesenfeld, and Andrew Gelfand. "Statistical comparison of a hybrid approach with approximate and exact inference models for Fusion 2+." In Defense and Security Symposium, edited by Ivan Kadar. SPIE, 2007. http://dx.doi.org/10.1117/12.717398.

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Lee, Nian-Ze, Yen-Shi Wang, and Jie-Hong R. Jiang. "Solving Stochastic Boolean Satisfiability under Random-Exist Quantification." In Twenty-Sixth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/96.

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Stochastic Boolean Satisfiability (SSAT) is a powerful formalism to represent computational problems with uncertainly, such as belief network inference and propositional probabilistic planning. Solving SSAT formulas lies in the same complexity class (PSPACE-complete) as solving Quantified Boolean Formula (QBF). While many endeavors have been made to enhance QBF solving, SSAT has drawn relatively less attention in recent years. This paper focuses on random-exist quantified SSAT formulas, and proposes an algorithm combining binary decision diagram (BDD), logic synthesis, and modern SAT technique
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Tian, Zheng, Ying Wen, Zhichen Gong, Faiz Punakkath, Shihao Zou, and Jun Wang. "A Regularized Opponent Model with Maximum Entropy Objective." 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.2019/85.

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In a single-agent setting, reinforcement learning (RL) tasks can be cast into an inference problem by introducing a binary random variable o, which stands for the "optimality". In this paper, we redefine the binary random variable o in multi-agent setting and formalize multi-agent reinforcement learning (MARL) as probabilistic inference. We derive a variational lower bound of the likelihood of achieving the optimality and name it as Regularized Opponent Model with Maximum Entropy Objective (ROMMEO). From ROMMEO, we present a novel perspective on opponent modeling and show how it can improve th
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Allphin, Devin, and Joshua Hamel. "A Parallel Offline CFD and Closed-Form Approximation Strategy for Computationally Efficient Analysis of Complex Fluid Flows." In ASME 2014 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/imece2014-38691.

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Computational fluid dynamics (CFD) solution approximations for complex fluid flow problems have become a common and powerful engineering analysis technique. These tools, though qualitatively useful, remain limited in practice by their underlying inverse relationship between simulation accuracy and overall computational expense. While a great volume of research has focused on remedying these issues inherent to CFD, one traditionally overlooked area of resource reduction for engineering analysis concerns the basic definition and determination of functional relationships for the studied fluid flo
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Jha, Chandan Kumar, and Joycee Mekie. "SEDA - Single Exact Dual Approximate Adders for Approximate Processors." In DAC '19: The 56th Annual Design Automation Conference 2019. ACM, 2019. http://dx.doi.org/10.1145/3316781.3322475.

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Yeredor, Arie. "On hybrid exact-approximate joint diagonalization." In 2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP). IEEE, 2009. http://dx.doi.org/10.1109/camsap.2009.5413271.

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Informes sobre el tema "Exact and approximate inferences"

1

Mobley, Curtis D. Ecosystem Predictions with Approximate vs. Exact Light Fields. Defense Technical Information Center, 2009. http://dx.doi.org/10.21236/ada495652.

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Mobley, Curtis D. Ecosystem Predictions with Approximate vs. Exact Light Fields. Defense Technical Information Center, 2008. http://dx.doi.org/10.21236/ada519107.

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Boland, Matthew R. Examination of the Use of Exact Versus Approximate Phase Weights on the Performance of a Synthetic Aperture Sonar System. Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada414590.

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Zarrieß, Benjamin, and Anni-Yasmin Turhan. Most Specific Generalizations w.r.t. General EL-TBoxes. Technische Universität Dresden, 2013. http://dx.doi.org/10.25368/2022.196.

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In the area of Description Logics the least common subsumer (lcs) and the most specific concept (msc) are inferences that generalize a set of concepts or an individual, respectively, into a single concept. If computed w.r.t. a general EL-TBox neither the lcs nor the msc need to exist. So far in this setting no exact conditions for the existence of lcs- or msc-concepts are known. This report provides necessary and suffcient conditions for the existence of these two kinds of concepts. For the lcs of a fixed number of concepts and the msc we show decidability of the existence in PTime and polynom
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Baader, Franz, and Oliver Fernández Gil. Decidability and Complexity of Threshold Description Logics Induced by Concept Similarity Measures. Technische Universität Dresden, 2016. http://dx.doi.org/10.25368/2022.229.

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In a recent research paper, we have proposed an extension of the lightweight Description Logic (DL) EL in which concepts can be defined in an approximate way. To this purpose, the notion of a graded membership function m, which instead of a Boolean membership value 0 or 1 yields a membership degree from the interval [0; 1], was introduced. Threshold concepts can then, for example, require that an individual belongs to a concept C with degree at least 0:8. Reasoning in the threshold DL T EL(m) obtained this way of course depends on the employed graded membership function m. The paper defines a
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Allegheny woodrat and eastern small-footed bat inventory: White Rocks ? Cumberland Gap National Historical Park. National Park Service, 2024. http://dx.doi.org/10.36967/2302513.

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Surveys were conducted for the presence of Allegheny woodrats, eastern small-footed bats, and their habitat within Sample Units surrounding potential climbing routes on the White Rocks cliff of Cumberland Gap National Historical Park. White Rocks is a 200-300ft south facing cliff along the Virginia- Kentucky border that contains the typical habitat requirements of both species: rock ledges, outcrops, or a network of fissures and crevices surrounded by forested habitat. The eastern small-footed bat uses this type of habitat primarily during the summer months for roosting while the Allegheny woo
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