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Bayesian inference of state space models : Kalman filtering and beyond / / Kostas Triantafyllopoulos
| Bayesian inference of state space models : Kalman filtering and beyond / / Kostas Triantafyllopoulos |
| Autore | Triantafyllopoulos Kostas |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer International Publishing, , [2021] |
| Descrizione fisica | 1 online resource (503 pages) |
| Disciplina | 629.8312 |
| Collana | Springer Texts in Statistics |
| Soggetto topico |
Kalman filtering
Bayesian statistical decision theory - Data processing Filtre de Kalman Estadística bayesiana |
| Soggetto genere / forma | Llibres electrònics |
| ISBN |
9783030761240
9783030761233 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996466563103316 |
Triantafyllopoulos Kostas
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| Cham, Switzerland : , : Springer International Publishing, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Bayesian inference of state space models : Kalman filtering and beyond / / Kostas Triantafyllopoulos
| Bayesian inference of state space models : Kalman filtering and beyond / / Kostas Triantafyllopoulos |
| Autore | Triantafyllopoulos Kostas |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer International Publishing, , [2021] |
| Descrizione fisica | 1 online resource (503 pages) |
| Disciplina | 629.8312 |
| Collana | Springer Texts in Statistics |
| Soggetto topico |
Kalman filtering
Bayesian statistical decision theory - Data processing Filtre de Kalman Estadística bayesiana |
| Soggetto genere / forma | Llibres electrònics |
| ISBN |
9783030761240
9783030761233 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910508435103321 |
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Triantafyllopoulos Kostas
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| Cham, Switzerland : , : Springer International Publishing, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Bayesian Networks : Advances and Novel Applications / / Douglas McNair, editor
| Bayesian Networks : Advances and Novel Applications / / Douglas McNair, editor |
| Pubbl/distr/stampa | London : , : IntechOpen, , [2019] |
| Descrizione fisica | 1 online resource (136 pages) : illustrations |
| Disciplina | 519.542 |
| Soggetto topico |
Bayesian statistical decision theory - Data processing
Mathematical statistics |
| ISBN |
1-83962-324-1
1-83962-323-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Bayesian networks |
| Record Nr. | UNINA-9910407753903321 |
| London : , : IntechOpen, , [2019] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Bayesian Optimization : Theory and Practice Using Python / / by Peng Liu
| Bayesian Optimization : Theory and Practice Using Python / / by Peng Liu |
| Autore | Liu Peng <1951-> |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Berkeley, CA : , : Apress : , : Imprint : Apress, , 2023 |
| Descrizione fisica | 1 online resource (243 pages) |
| Disciplina | 519.54202855133 |
| Soggetto topico |
Bayesian statistical decision theory - Data processing
Python (Computer program language) Mathematical optimization |
| ISBN | 1-4842-9063-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1: Bayesian Optimization Overview -- Chapter 2: Gaussian Process -- Chapter 3: Bayesian Decision Theory and Expected Improvement -- Chapter 4 : Gaussian Process Regression with GPyTorch -- Chapter 5: Monte Carlo Acquisition Function with Sobol Sequences and Random Restart -- Chapter 6 : Knowledge Gradient: Nested Optimization versus One-shot Learning -- Chapter 7 : Case Study: Tuning CNN Learning Rate with BoTorch. |
| Record Nr. | UNINA-9910683362603321 |
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Liu Peng <1951->
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| Berkeley, CA : , : Apress : , : Imprint : Apress, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Probabilistic methods for financial and marketing informatics [[electronic resource] /] / Richard E. Neapolitan, Xia Jiang
| Probabilistic methods for financial and marketing informatics [[electronic resource] /] / Richard E. Neapolitan, Xia Jiang |
| Autore | Neapolitan Richard E |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | San Fransisco, CA, : Morgan Kaufmann Publishers, c2007 |
| Descrizione fisica | 1 online resource (427 p.) |
| Disciplina | 332.01/519542 |
| Altri autori (Persone) | JiangXia |
| Soggetto topico |
Finance - Statistical methods
Bayesian statistical decision theory - Data processing Marketing - Statistical methods Information technology |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-281-31147-2
9786611311476 0-08-055567-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Probabilistic Methods for Financial and Marketing Informatics; Copyright Page; Preface; Contents; Part I: Bayesian Networks and Decision Analysis; Chapter 1. Probabilistic Informatics; 1.1 What Is Informatics?; 1.2 Probabilistic Informatics; 1.3 Outline of This Book; Chapter 2. Probability and Statistics; 2.1 Probability Basics; 2.2 Random Variables; 2.3 The Meaning of Probability; 2.4 Random Variables in Applications; 2.5 Statistical Concepts; Chapter 3. Bayesian Networks; 3.1 What Is a Bayesian Network?; 3.2 Properties of Bayesian Networks
3.3 Causal Networks as Bayesian Networks 3.4 Inference in Bayesian Networks; 3.5 How Do We Obtain the Probabilities?; 3.6 Entailed Conditional Independencies *; Chapter 4. Learning Bayesian Networks; 4.1 Parameter Learning; 4.2 Learning Structure (Model Selection); 4.3 Score-Based Structure Learning *; 4.4 Constraint-Based Structure Learning; 4.5 Causal Learning; 4.6 Software Packages for Learning; 4.7 Examples of Learning; Chapter 5. Decision Analysis Fundamentals; 5.1 Decision Trees; 5.2 Influence Diagrams; 5.3 Dynamic Networks *; Chapter 6. Further Techniques in Decision Analysis 6.1 Modeling Risk Preferences 6.2 Analyzing Risk Directly; 6.3 Dominance; 6.4 Sensitivity Analysis; 6.5 Value of Information; 6.6 Normative Decision Analysis; Part II: Financial Applications; Chapter 7. Investment Science; 7.1 Basics of Investment Science; 7.2 Advanced Topics in Investment Science*; 7.3 A Bayesian Network Portfolio Risk Analyzer *; Chapter 8. Modeling Real Options; 8.1 Solving Real Options Decision Problems; 8.2 Making a Plan; 8.3 Sensitivity Analysis; Chapter 9. Venture Capital Decision Making; 9.1 A Simple VC Decision Model; 9.2 A Detailed VC Decision Model 9.3 Modeling Real Decisions 9.A Appendix; Chapter 10. Bankruptcy Prediction; 10.1 A Bayesian Network for Predicting Bankruptcy; 10.2 Experiments; Part III: Marketing Applications; Chapter 11. Collaborative Filtering; 11.1 Memory-Based Methods; 11.2 Model-Based Methods; 11.3 Experiments; Chapter 12. Targeted Advertising; 12.1 Class Probability Trees; 12.2 Application to Targeted Advertising; Bibliography; Index |
| Record Nr. | UNINA-9910458845103321 |
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Neapolitan Richard E
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| San Fransisco, CA, : Morgan Kaufmann Publishers, c2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Probabilistic methods for financial and marketing informatics [[electronic resource] /] / Richard E. Neapolitan, Xia Jiang
| Probabilistic methods for financial and marketing informatics [[electronic resource] /] / Richard E. Neapolitan, Xia Jiang |
| Autore | Neapolitan Richard E |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | San Fransisco, CA, : Morgan Kaufmann Publishers, c2007 |
| Descrizione fisica | 1 online resource (427 p.) |
| Disciplina | 332.01/519542 |
| Altri autori (Persone) | JiangXia |
| Soggetto topico |
Finance - Statistical methods
Bayesian statistical decision theory - Data processing Marketing - Statistical methods Information technology |
| ISBN |
1-281-31147-2
9786611311476 0-08-055567-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Probabilistic Methods for Financial and Marketing Informatics; Copyright Page; Preface; Contents; Part I: Bayesian Networks and Decision Analysis; Chapter 1. Probabilistic Informatics; 1.1 What Is Informatics?; 1.2 Probabilistic Informatics; 1.3 Outline of This Book; Chapter 2. Probability and Statistics; 2.1 Probability Basics; 2.2 Random Variables; 2.3 The Meaning of Probability; 2.4 Random Variables in Applications; 2.5 Statistical Concepts; Chapter 3. Bayesian Networks; 3.1 What Is a Bayesian Network?; 3.2 Properties of Bayesian Networks
3.3 Causal Networks as Bayesian Networks 3.4 Inference in Bayesian Networks; 3.5 How Do We Obtain the Probabilities?; 3.6 Entailed Conditional Independencies *; Chapter 4. Learning Bayesian Networks; 4.1 Parameter Learning; 4.2 Learning Structure (Model Selection); 4.3 Score-Based Structure Learning *; 4.4 Constraint-Based Structure Learning; 4.5 Causal Learning; 4.6 Software Packages for Learning; 4.7 Examples of Learning; Chapter 5. Decision Analysis Fundamentals; 5.1 Decision Trees; 5.2 Influence Diagrams; 5.3 Dynamic Networks *; Chapter 6. Further Techniques in Decision Analysis 6.1 Modeling Risk Preferences 6.2 Analyzing Risk Directly; 6.3 Dominance; 6.4 Sensitivity Analysis; 6.5 Value of Information; 6.6 Normative Decision Analysis; Part II: Financial Applications; Chapter 7. Investment Science; 7.1 Basics of Investment Science; 7.2 Advanced Topics in Investment Science*; 7.3 A Bayesian Network Portfolio Risk Analyzer *; Chapter 8. Modeling Real Options; 8.1 Solving Real Options Decision Problems; 8.2 Making a Plan; 8.3 Sensitivity Analysis; Chapter 9. Venture Capital Decision Making; 9.1 A Simple VC Decision Model; 9.2 A Detailed VC Decision Model 9.3 Modeling Real Decisions 9.A Appendix; Chapter 10. Bankruptcy Prediction; 10.1 A Bayesian Network for Predicting Bankruptcy; 10.2 Experiments; Part III: Marketing Applications; Chapter 11. Collaborative Filtering; 11.1 Memory-Based Methods; 11.2 Model-Based Methods; 11.3 Experiments; Chapter 12. Targeted Advertising; 12.1 Class Probability Trees; 12.2 Application to Targeted Advertising; Bibliography; Index |
| Record Nr. | UNINA-9910784616403321 |
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Neapolitan Richard E
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||
| San Fransisco, CA, : Morgan Kaufmann Publishers, c2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Probabilistic methods for financial and marketing informatics / / Richard E. Neapolitan, Xia Jiang
| Probabilistic methods for financial and marketing informatics / / Richard E. Neapolitan, Xia Jiang |
| Autore | Neapolitan Richard E |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | San Fransisco, CA, : Morgan Kaufmann Publishers, c2007 |
| Descrizione fisica | 1 online resource (427 p.) |
| Disciplina | 332.01/519542 |
| Altri autori (Persone) | JiangXia |
| Soggetto topico |
Finance - Statistical methods
Bayesian statistical decision theory - Data processing Marketing - Statistical methods Information technology |
| ISBN |
1-281-31147-2
9786611311476 0-08-055567-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Probabilistic Methods for Financial and Marketing Informatics; Copyright Page; Preface; Contents; Part I: Bayesian Networks and Decision Analysis; Chapter 1. Probabilistic Informatics; 1.1 What Is Informatics?; 1.2 Probabilistic Informatics; 1.3 Outline of This Book; Chapter 2. Probability and Statistics; 2.1 Probability Basics; 2.2 Random Variables; 2.3 The Meaning of Probability; 2.4 Random Variables in Applications; 2.5 Statistical Concepts; Chapter 3. Bayesian Networks; 3.1 What Is a Bayesian Network?; 3.2 Properties of Bayesian Networks
3.3 Causal Networks as Bayesian Networks 3.4 Inference in Bayesian Networks; 3.5 How Do We Obtain the Probabilities?; 3.6 Entailed Conditional Independencies *; Chapter 4. Learning Bayesian Networks; 4.1 Parameter Learning; 4.2 Learning Structure (Model Selection); 4.3 Score-Based Structure Learning *; 4.4 Constraint-Based Structure Learning; 4.5 Causal Learning; 4.6 Software Packages for Learning; 4.7 Examples of Learning; Chapter 5. Decision Analysis Fundamentals; 5.1 Decision Trees; 5.2 Influence Diagrams; 5.3 Dynamic Networks *; Chapter 6. Further Techniques in Decision Analysis 6.1 Modeling Risk Preferences 6.2 Analyzing Risk Directly; 6.3 Dominance; 6.4 Sensitivity Analysis; 6.5 Value of Information; 6.6 Normative Decision Analysis; Part II: Financial Applications; Chapter 7. Investment Science; 7.1 Basics of Investment Science; 7.2 Advanced Topics in Investment Science*; 7.3 A Bayesian Network Portfolio Risk Analyzer *; Chapter 8. Modeling Real Options; 8.1 Solving Real Options Decision Problems; 8.2 Making a Plan; 8.3 Sensitivity Analysis; Chapter 9. Venture Capital Decision Making; 9.1 A Simple VC Decision Model; 9.2 A Detailed VC Decision Model 9.3 Modeling Real Decisions 9.A Appendix; Chapter 10. Bankruptcy Prediction; 10.1 A Bayesian Network for Predicting Bankruptcy; 10.2 Experiments; Part III: Marketing Applications; Chapter 11. Collaborative Filtering; 11.1 Memory-Based Methods; 11.2 Model-Based Methods; 11.3 Experiments; Chapter 12. Targeted Advertising; 12.1 Class Probability Trees; 12.2 Application to Targeted Advertising; Bibliography; Index |
| Record Nr. | UNINA-9910828813603321 |
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Neapolitan Richard E
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| San Fransisco, CA, : Morgan Kaufmann Publishers, c2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Probabilistic reasoning in multiagent systems : a graphical models approach / / Yang Xiang [[electronic resource]]
| Probabilistic reasoning in multiagent systems : a graphical models approach / / Yang Xiang [[electronic resource]] |
| Autore | Xiang Yang <1954-> |
| Pubbl/distr/stampa | Cambridge : , : Cambridge University Press, , 2002 |
| Descrizione fisica | 1 online resource (xii, 294 pages) : digital, PDF file(s) |
| Disciplina | 006.3 |
| Soggetto topico |
Distributed artificial intelligence
Bayesian statistical decision theory - Data processing Multiagent systems |
| ISBN |
1-107-13315-7
0-521-15390-5 1-280-43403-1 9786610434039 0-511-17772-0 0-511-14812-7 0-511-30516-8 0-511-54693-9 0-511-04544-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Intelligent Agents -- Reasoning about the Environment -- Why Uncertain Reasoning? -- Multiagent Systems -- Cooperative Multiagent Probabilistic Reasoning -- Application Domains -- Bayesian Networks -- Basics on Bayesian Probability Theory -- Belief Updating Using JPD -- Graphs -- Local Computation and Message Passing -- Message Passing over Multiple Networks -- Approximation with Massive Message Passing -- Belief Updating and Cluster Graphs -- Conventions for Message Passing in Cluster Graphs -- Relation with [lambda] -- [pi] Message Passing -- Message Passing in Nondegenerate Cycles -- Message Passing in Degenerate Cycles -- Junction Trees -- Junction Tree Representation -- Graphical Separation -- Sufficient Message and Independence -- Encoding Independence in Graphs -- Junction Trees and Chordal Graphs -- Triangulation by Elimination -- Junction Trees as I-maps -- Junction Tree Construction -- Belief Updating with Junction Trees -- Algebraic Properties of Potentials -- Potential Assignment in Junction Trees -- Passing Belief over Separators -- Passing Belief through a Junction Tree -- Processing Observations -- Multiply Sectioned Bayesian Networks -- The Task of Distributed Uncertain Reasoning -- Organization of Agents during Communication -- Agent Interface -- Multiagent Dependence Structure -- Linked Junction Forests -- Multiagent Distributed Compilation of MSBNs -- Multiagent Moralization of MSDAG -- Effective Communication Using Linkage Trees -- Linkage Trees as I-maps -- Multiagent Triangulation. |
| Record Nr. | UNINA-9910456188103321 |
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Xiang Yang <1954->
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| Cambridge : , : Cambridge University Press, , 2002 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Probabilistic reasoning in multiagent systems : a graphical models approach / / Yang Xiang [[electronic resource]]
| Probabilistic reasoning in multiagent systems : a graphical models approach / / Yang Xiang [[electronic resource]] |
| Autore | Xiang Yang <1954-> |
| Pubbl/distr/stampa | Cambridge : , : Cambridge University Press, , 2002 |
| Descrizione fisica | 1 online resource (xii, 294 pages) : digital, PDF file(s) |
| Disciplina | 006.3 |
| Soggetto topico |
Distributed artificial intelligence
Bayesian statistical decision theory - Data processing Multiagent systems |
| ISBN |
1-107-13315-7
0-521-15390-5 1-280-43403-1 9786610434039 0-511-17772-0 0-511-14812-7 0-511-30516-8 0-511-54693-9 0-511-04544-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Intelligent Agents -- Reasoning about the Environment -- Why Uncertain Reasoning? -- Multiagent Systems -- Cooperative Multiagent Probabilistic Reasoning -- Application Domains -- Bayesian Networks -- Basics on Bayesian Probability Theory -- Belief Updating Using JPD -- Graphs -- Local Computation and Message Passing -- Message Passing over Multiple Networks -- Approximation with Massive Message Passing -- Belief Updating and Cluster Graphs -- Conventions for Message Passing in Cluster Graphs -- Relation with [lambda] -- [pi] Message Passing -- Message Passing in Nondegenerate Cycles -- Message Passing in Degenerate Cycles -- Junction Trees -- Junction Tree Representation -- Graphical Separation -- Sufficient Message and Independence -- Encoding Independence in Graphs -- Junction Trees and Chordal Graphs -- Triangulation by Elimination -- Junction Trees as I-maps -- Junction Tree Construction -- Belief Updating with Junction Trees -- Algebraic Properties of Potentials -- Potential Assignment in Junction Trees -- Passing Belief over Separators -- Passing Belief through a Junction Tree -- Processing Observations -- Multiply Sectioned Bayesian Networks -- The Task of Distributed Uncertain Reasoning -- Organization of Agents during Communication -- Agent Interface -- Multiagent Dependence Structure -- Linked Junction Forests -- Multiagent Distributed Compilation of MSBNs -- Multiagent Moralization of MSDAG -- Effective Communication Using Linkage Trees -- Linkage Trees as I-maps -- Multiagent Triangulation. |
| Record Nr. | UNINA-9910780283503321 |
|
Xiang Yang <1954->
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||
| Cambridge : , : Cambridge University Press, , 2002 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Probabilistic reasoning in multiagent systems : a graphical models approach / / Yang Xiang
| Probabilistic reasoning in multiagent systems : a graphical models approach / / Yang Xiang |
| Autore | Xiang Yang <1954-> |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cambridge ; ; New York, : Cambridge University Press, 2002 |
| Descrizione fisica | 1 online resource (xii, 294 pages) : digital, PDF file(s) |
| Disciplina | 006.3 |
| Soggetto topico |
Distributed artificial intelligence
Bayesian statistical decision theory - Data processing Intelligent agents (Computer software) |
| ISBN |
1-107-13315-7
0-521-15390-5 1-280-43403-1 9786610434039 0-511-17772-0 0-511-14812-7 0-511-30516-8 0-511-54693-9 0-511-04544-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Intelligent Agents -- Reasoning about the Environment -- Why Uncertain Reasoning? -- Multiagent Systems -- Cooperative Multiagent Probabilistic Reasoning -- Application Domains -- Bayesian Networks -- Basics on Bayesian Probability Theory -- Belief Updating Using JPD -- Graphs -- Local Computation and Message Passing -- Message Passing over Multiple Networks -- Approximation with Massive Message Passing -- Belief Updating and Cluster Graphs -- Conventions for Message Passing in Cluster Graphs -- Relation with [lambda] -- [pi] Message Passing -- Message Passing in Nondegenerate Cycles -- Message Passing in Degenerate Cycles -- Junction Trees -- Junction Tree Representation -- Graphical Separation -- Sufficient Message and Independence -- Encoding Independence in Graphs -- Junction Trees and Chordal Graphs -- Triangulation by Elimination -- Junction Trees as I-maps -- Junction Tree Construction -- Belief Updating with Junction Trees -- Algebraic Properties of Potentials -- Potential Assignment in Junction Trees -- Passing Belief over Separators -- Passing Belief through a Junction Tree -- Processing Observations -- Multiply Sectioned Bayesian Networks -- The Task of Distributed Uncertain Reasoning -- Organization of Agents during Communication -- Agent Interface -- Multiagent Dependence Structure -- Linked Junction Forests -- Multiagent Distributed Compilation of MSBNs -- Multiagent Moralization of MSDAG -- Effective Communication Using Linkage Trees -- Linkage Trees as I-maps -- Multiagent Triangulation. |
| Record Nr. | UNINA-9910819497103321 |
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Xiang Yang <1954->
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| Cambridge ; ; New York, : Cambridge University Press, 2002 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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