Probabilistic Graphical Models (Record no. 54918)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 05216nam a22005655i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-319-11433-0 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20200421111659.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 140911s2014 gw | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9783319114330 |
| -- | 978-3-319-11433-0 |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 006.3 |
| 245 10 - TITLE STATEMENT | |
| Title | Probabilistic Graphical Models |
| Sub Title | 7th European Workshop, PGM 2014, Utrecht, The Netherlands, September 17-19, 2014. Proceedings / |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | XII, 598 p. 186 illus. |
| 490 1# - SERIES STATEMENT | |
| Series statement | Lecture Notes in Computer Science, |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Remark 2 | Structural Sensitivity for the Knowledge Engineering of Bayesian Networks -- A Pairwise Class Interaction Framework for Multilabel Classification -- From Information to Evidence in a Bayesian Network -- Learning Gated Bayesian Networks for Algorithmic Trading -- Local Sensitivity of Bayesian Networks to Multiple Simultaneous Parameter Shifts -- Bayesian Network Inference Using Marginal Trees -- On SPI-Lazy Evaluation of Influence Diagrams -- Extended Probability Trees for Probabilistic Graphical Models -- Mixture of Polynomials Probability Distributions for Grouped Sample Data -- Trading off Speed and Accuracy in Multilabel Classification -- Robustifying the Viterbi algorithm -- Extended Tree Augmented Naive Classifier -- Evaluation of Rules for Coping with Insufficient Data in Constraint-based Search Algorithms -- Supervised Classification Using Hybrid Probabilistic Decision Graphs -- Towards a Bayesian Decision Theoretic Analysis of Contextual Effect Modifiers -- Discrete Bayesian Network Interpretation of the Cox's Proportional Hazards Model -- Minimizing Relative Entropy in Hierarchical Predictive Coding -- Treewidth and the Computational Complexity of MAP Approximations -- Bayesian Networks with Function Nodes -- A New Method for Vertical Parallelisation of TAN Learning Based on Balanced Incomplete Block Designs -- Equivalences Between Maximum A Posteriori Inference in Bayesian Networks and Maximum Expected Utility Computation in Influence Diagrams -- Speeding Up $k$-Neighborhood Local Search in Limited Memory Influence Diagrams -- Inhibited Effects in CP-logic -- Learning Parameters in Canonical Models using Weighted Least Squares -- Learning Marginal AMP Chain Graphs under Faithfulness -- Learning Maximum Weighted (k+1)-order Decomposable Graphs by Integer Linear Programming -- Multi-label Classification for Tree and Directed Acyclic Graphs Hierarchies -- Min-BDeu and Max-BDeu Scores for Learning Bayesian Networks -- Causal Discovery from Databases with Discrete and Continuous Variables -- On Expressiveness of the AMP Chain Graph Interpretation -- Learning Bayesian Network Structures when Discrete and Continuous Variables are Present -- Learning Neighborhoods of High Confidence in Constraint-Based Causal Discovery -- Causal Independence Models for Continuous Time Bayesian Networks -- Expressive Power of Binary Relevance and Chain Classifiers Based on Bayesian Networks for Multi-Label Classification -- An Approximate Tensor-Based Inference Method Applied to the Game of Minesweeper -- Compression of Bayesian Networks with NIN-AND Tree Modeling -- A Study of Recently Discovered Equalities about Latent Tree Models using Inverse Edges -- An Extended MPL-C Model for Bayesian Network Parameter Learning with Exterior Constraints. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | This book constitutes the refereed proceedings of the 7th International Workshop on Probabilistic Graphical Models, PGM 2014, held in Utrecht, The Netherlands, in September 2014. The 38 revised full papers presented in this book were carefully reviewed and selected from 44 submissions. The papers cover all aspects of graphical models for probabilistic reasoning, decision making, and learning. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| General subdivision | Mathematics. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Gaag, Linda C. van der. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Feelders, Ad J. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | http://dx.doi.org/10.1007/978-3-319-11433-0 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | Cham : |
| -- | Springer International Publishing : |
| -- | Imprint: Springer, |
| -- | 2014. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
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| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
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| -- | rda |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer science. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer science |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Mathematical statistics. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Data mining. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Artificial intelligence. |
| 650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer Science. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Artificial Intelligence (incl. Robotics). |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Probability and Statistics in Computer Science. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Data Mining and Knowledge Discovery. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Discrete Mathematics in Computer Science. |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| -- | 0302-9743 ; |
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| -- | ZDB-2-SCS |
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