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Constrained Conditional Model
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Book Synopsis Constrained Conditional Model by : Fouad Sabry
Download or read book Constrained Conditional Model written by Fouad Sabry and published by One Billion Knowledgeable. This book was released on 2023-07-04 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: What Is Constrained Conditional Model A constrained conditional model, also known as a constrained conditional model (CCM), is a paradigm for machine learning and inference that enhances the learning of conditional models by applying declarative constraints. It is possible to utilize the constraint as a mechanism for incorporating expressive prior knowledge into the model and for instructing the learnt model to bias the assignments it generates to satisfy the constraints. While preserving the modularity and tractability of training and inference, the framework may be utilized to enable decisions in an expressive output space. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Constrained conditional model Chapter 2: Machine learning Chapter 3: Natural language processing Chapter 4: Natural language generation Chapter 5: Feature engineering Chapter 6: Constrained optimization Chapter 7: Textual entailment Chapter 8: Transliteration Chapter 9: Structured prediction Chapter 10: Semantic role labeling (II) Answering the public top questions about constrained conditional model. (III) Real world examples for the usage of constrained conditional model in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of constrained conditional model' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of constrained conditional model.
Book Synopsis Constrained Conditional Moment Restriction Models by : Victor Chernozhukov
Download or read book Constrained Conditional Moment Restriction Models written by Victor Chernozhukov and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Shape restrictions have played a central role in economics as both testable implications of theory and sufficient conditions for obtaining informative counterfactual predictions. In this paper we provide a general procedure for inference under shape restrictions in identified and partially identified models defined by conditional moment restrictions. Our test statistics and proposed inference methods are based on the minimum of the generalized method of moments (GMM) objective function with and without shape restrictions. Uniformly valid critical values are obtained through a bootstrap procedure that approximates a subset of the true local parameter space. In an empirical analysis of the effect of childbearing on female labor supply, we show that employing shape restrictions in linear instrumental variables (IV) models can lead to shorter confidence regions for both local and average treatment effects. Other applications we discuss include inference for the variability of quantile IV treatment effects and for bounds on average equivalent variation in a demand model with general heterogeneity. We find in Monte Carlo examples that the critical values are conservatively accurate and that tests about objects of interest have good power relative to unrestricted GMM.
Book Synopsis Aimms Optimization Modeling by : Johannes Bisschop
Download or read book Aimms Optimization Modeling written by Johannes Bisschop and published by Lulu.com. This book was released on 2006 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: The AIMMS Optimization Modeling book provides not only an introduction to modeling but also a suite of worked examples. It is aimed at users who are new to modeling and those who have limited modeling experience. Both the basic concepts of optimization modeling and more advanced modeling techniques are discussed. The Optimization Modeling book is AIMMS version independent.
Book Synopsis Constrained Markov Decision Processes by : Eitan Altman
Download or read book Constrained Markov Decision Processes written by Eitan Altman and published by Routledge. This book was released on 2021-12-17 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a unified approach for the study of constrained Markov decision processes with a finite state space and unbounded costs. Unlike the single controller case considered in many other books, the author considers a single controller with several objectives, such as minimizing delays and loss, probabilities, and maximization of throughputs. It is desirable to design a controller that minimizes one cost objective, subject to inequality constraints on other cost objectives. This framework describes dynamic decision problems arising frequently in many engineering fields. A thorough overview of these applications is presented in the introduction. The book is then divided into three sections that build upon each other.
Book Synopsis Constrained Clustering by : Sugato Basu
Download or read book Constrained Clustering written by Sugato Basu and published by CRC Press. This book was released on 2008-08-18 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the initial work on constrained clustering, there have been numerous advances in methods, applications, and our understanding of the theoretical properties of constraints and constrained clustering algorithms. Bringing these developments together, Constrained Clustering: Advances in Algorithms, Theory, and Applications presents an extensive collection of the latest innovations in clustering data analysis methods that use background knowledge encoded as constraints. Algorithms The first five chapters of this volume investigate advances in the use of instance-level, pairwise constraints for partitional and hierarchical clustering. The book then explores other types of constraints for clustering, including cluster size balancing, minimum cluster size,and cluster-level relational constraints. Theory It also describes variations of the traditional clustering under constraints problem as well as approximation algorithms with helpful performance guarantees. Applications The book ends by applying clustering with constraints to relational data, privacy-preserving data publishing, and video surveillance data. It discusses an interactive visual clustering approach, a distance metric learning approach, existential constraints, and automatically generated constraints. With contributions from industrial researchers and leading academic experts who pioneered the field, this volume delivers thorough coverage of the capabilities and limitations of constrained clustering methods as well as introduces new types of constraints and clustering algorithms.
Book Synopsis Constrained Statistical Inference by : Mervyn J. Silvapulle
Download or read book Constrained Statistical Inference written by Mervyn J. Silvapulle and published by John Wiley & Sons. This book was released on 2011-09-15 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: An up-to-date approach to understanding statistical inference Statistical inference is finding useful applications in numerous fields, from sociology and econometrics to biostatistics. This volume enables professionals in these and related fields to master the concepts of statistical inference under inequality constraints and to apply the theory to problems in a variety of areas. Constrained Statistical Inference: Order, Inequality, and Shape Constraints provides a unified and up-to-date treatment of the methodology. It clearly illustrates concepts with practical examples from a variety of fields, focusing on sociology, econometrics, and biostatistics. The authors also discuss a broad range of other inequality-constrained inference problems that do not fit well in the contemplated unified framework, providing a meaningful way for readers to comprehend methodological resolutions. Chapter coverage includes: Population means and isotonic regression Inequality-constrained tests on normal means Tests in general parametric models Likelihood and alternatives Analysis of categorical data Inference on monotone density function, unimodal density function, shape constraints, and DMRL functions Bayesian perspectives, including Stein’s Paradox, shrinkage estimation, and decision theory
Book Synopsis Conditional and Composite (temporal) CSPs by : Amrudee Sukpan
Download or read book Conditional and Composite (temporal) CSPs written by Amrudee Sukpan and published by . This book was released on 2008 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose the Conditional and Composite Constraint Satisfaction Problem (CCCSP) model, a unique framework to efficiently manage dynamic CSPs where dynamic sets of variables and constraints are known under predefined conditions. Two resolution techniques for solving CCCSPs: (1) complete methods based on constraint propagations and (2) incomplete methods based on Stochastic Local Search (SLS), have been developed. The CCCSP framework is augmented to encode numeric and symbolic temporal constraints. The new temporal model is called Conditional and Composite Temporal Constraint Satisfaction Problem (CCTCSP). In addition, the CCCSP resolution methods have been adapted for solving CCTCSPs. In the case of searching for the preferred solution according to a given objective function, preferences defined at different levels of CCCSPs and CCTCSPs indicate degrees of satisfaction and are treated as soft constraints. In order to handle these preferences, the CCCSP and the CCTCSP frameworks are extended with the c-semiring, and the complete solving methods are modified following the Branch and Bound technique. CCCSPs and CCTCSPs with preferences can be applied to applications such as configuration problems, planning and scheduling problems, software designs and expert systems. The proposed algorithms are compared using an extensive experimental study over randomly generated problems. The experimental results demonstrate that in the case of hard problems (i.e., middle constrained and highly dynamic structured instances), our complete solving methods with the advanced constraint propagation techniques outperform the general ones while obtaining the same results. The results also show that, the incomplete methods using SLS techniques are faster than the complete ones in the case of hard problems. These SLS techniques are relevant in case we want to trade the quality of solutions for the time efficiency.
Book Synopsis Algorithms for Solving Dynamic Models with Occasionally Binding Constraints by : Lawrence J. Christiano
Download or read book Algorithms for Solving Dynamic Models with Occasionally Binding Constraints written by Lawrence J. Christiano and published by . This book was released on 1994 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Multivariate Models and Multivariate Dependence Concepts by : Harry Joe
Download or read book Multivariate Models and Multivariate Dependence Concepts written by Harry Joe and published by CRC Press. This book was released on 1997-05-01 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book on multivariate models, statistical inference, and data analysis contains deep coverage of multivariate non-normal distributions for modeling of binary, count, ordinal, and extreme value response data. It is virtually self-contained, and includes many exercises and unsolved problems.
Book Synopsis A Groundwater Management Model Using Conditional Simulation and Chance-constrained Optimization by : Jesús Alberto Rodríguez Castro
Download or read book A Groundwater Management Model Using Conditional Simulation and Chance-constrained Optimization written by Jesús Alberto Rodríguez Castro and published by . This book was released on 1994 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Proceedings of the Eighteenth Annual Conference of the Cognitive Science Society by : Garrison W. Cottrell
Download or read book Proceedings of the Eighteenth Annual Conference of the Cognitive Science Society written by Garrison W. Cottrell and published by Routledge. This book was released on 2019-02-21 with total page 908 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume features the complete text of all regular papers, posters, and summaries of symposia presented at the 18th annual meeting of the Cognitive Science Society. Papers have been loosely grouped by topic, and an author index is provided in the back. In hopes of facilitating searches of this work, an electronic index on the Internet's World Wide Web is provided. Titles, authors, and summaries of all the papers published here have been placed in an online database which may be freely searched by anyone. You can reach the Web site at: http://www.cse.ucsd.edu/events/cogsci96/proceedings. You may view the table of contents for this volume on the LEA Web site at: http://www.erlbaum.com.
Book Synopsis Modeling Financial Time Series with S-PLUS by : Eric Zivot
Download or read book Modeling Financial Time Series with S-PLUS written by Eric Zivot and published by Springer Science & Business Media. This book was released on 2003-09-12 with total page 648 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of financial econometrics has exploded since the early 1990s. This book represents an integration of theory, methods and examples using the S-PLUS statistical modeling language and the S+FinMetrics module to facilitate the practice of financial econometrics. It shows the power of S-PLUS for the analysis of time series data. It is written for researchers and practitioners in the finance industry, academic researchers in economics and finance, and advanced MBA and graduate students in economics and finance. Readers are assumed to have a basic knowledge of S-PLUS and a solid grounding in basic statistics and time series concepts.
Book Synopsis Pattern Recognition Applications and Methods by : Maria De Marsico
Download or read book Pattern Recognition Applications and Methods written by Maria De Marsico and published by Springer Nature. This book was released on 2023-01-26 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains revised and extended versions of selected papers from the 10th and 11th International Conference on Pattern Recognition, ICPRAM 2021 and 2022, held in February 2021 and 2022. Due to COVID-19 pandemic the conferences were held virtually. Both conferences received in total 204 submissions from which 8 full papers were carefully reviewed and selected for presentation in this volume. The papers span a wide range of investigation as well as development lines, which of course always reflect the last trends of research in the pattern recognition community.
Book Synopsis Some Special P-models in Chance-constrained Programming by : Abraham Charnes
Download or read book Some Special P-models in Chance-constrained Programming written by Abraham Charnes and published by . This book was released on 1965 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sufficient conditions are derived for decision rules to be optimal for two classes of n-period P-models of chance-constrained programming. It is shown that the optimal rule for period j is the optimal piecewise linear function of the decision rules of previous periods and certain fractile points. The optimal class of rules is shown to be the same for the n-period P-model as for the corresponding n-period E-model. (Author).
Book Synopsis Bayesian Evaluation of Informative Hypotheses by : Herbert Hoijtink
Download or read book Bayesian Evaluation of Informative Hypotheses written by Herbert Hoijtink and published by Springer Science & Business Media. This book was released on 2008-09-08 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of the developments in the area of Bayesian evaluation of informative hypotheses that took place since the publication of the ?rst paper on this topic in 2001 [Hoijtink, H. Con?rmatory latent class analysis, model selection using Bayes factors and (pseudo) likelihood ratio statistics. Multivariate Behavioral Research, 36, 563–588]. The current state of a?airs was presented and discussed by the authors of this book during a workshop in Utrecht in June 2007. Here we would like to thank all authors for their participation, ideas, and contributions. We would also like to thank Sophie van der Zee for her editorial e?orts during the construction of this book. Another word of thanks is due to John Kimmel of Springer for his con?dence in the editors and authors. Finally, we would like to thank the Netherlands Organization for Scienti?c Research (NWO) whose VICI grant (453-05-002) awarded to the ?rst author enabled the organization of the workshop, the writing of this book, and continuation of the research with respect to Bayesian evaluation of informative hypotheses.
Book Synopsis Multiple Regression and Beyond by : Timothy Z. Keith
Download or read book Multiple Regression and Beyond written by Timothy Z. Keith and published by Routledge. This book was released on 2014-12-19 with total page 807 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiple Regression and Beyond offers a conceptually oriented introduction to multiple regression (MR) analysis and structural equation modeling (SEM), along with analyses that flow naturally from those methods. By focusing on the concepts and purposes of MR and related methods, rather than the derivation and calculation of formulae, this book introduces material to students more clearly, and in a less threatening way. In addition to illuminating content necessary for coursework, the accessibility of this approach means students are more likely to be able to conduct research using MR or SEM--and more likely to use the methods wisely. Covers both MR and SEM, while explaining their relevance to one another Also includes path analysis, confirmatory factor analysis, and latent growth modeling Figures and tables throughout provide examples and illustrate key concepts and techniques For additional resources, please visit: http://tzkeith.com/
Book Synopsis Probabilistic Constrained Optimization by : Stanislav Uryasev
Download or read book Probabilistic Constrained Optimization written by Stanislav Uryasev and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probabilistic and percentile/quantile functions play an important role in several applications, such as finance (Value-at-Risk), nuclear safety, and the environment. Recently, significant advances have been made in sensitivity analysis and optimization of probabilistic functions, which is the basis for construction of new efficient approaches. This book presents the state of the art in the theory of optimization of probabilistic functions and several engineering and finance applications, including material flow systems, production planning, Value-at-Risk, asset and liability management, and optimal trading strategies for financial derivatives (options). Audience: The book is a valuable source of information for faculty, students, researchers, and practitioners in financial engineering, operation research, optimization, computer science, and related areas.
