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PGM 2016: Lugano, Switzerland
- Alessandro Antonucci, Giorgio Corani, Cassio Polpo de Campos:
Probabilistic Graphical Models - Eighth International Conference, PGM 2016, Lugano, Switzerland, September 6-9, 2016. Proceedings. JMLR Workshop and Conference Proceedings 52, JMLR.org 2016 - Marcus Bendtsen:
Regime Aware Learning. 1-12 - Marco Benjumeda, Concha Bielza, Pedro Larrañaga:
Learning Tractable Multidimensional Bayesian Network Classifiers. 13-24 - Bence Bolgár, Peter Antal:
Bayesian Matrix Factorization with Non-Random Missing Data using Informative Gaussian Process Priors and Soft Evidences. 25-36 - Janneke H. Bolt:
Bayesian Networks: a Combined Tuning Heuristic. 37-49 - Marcos L. P. Bueno, Arjen Hommersom, Peter J. F. Lucas, Sicco Verwer, Alexis Linard:
Learning Complex Uncertain States Changes via Asymmetric Hidden Markov Models: an Industrial Case. 50-61 - Cory J. Butz, Jhonatan de S. Oliveira, André E. dos Santos, Anders L. Madsen:
On Bayesian Network Inference with Simple Propagation. 62-73 - Cory J. Butz, André E. dos Santos, Jhonatan de S. Oliveira:
Relevant Path Separation: A Faster Method for Testing Independencies in Bayesian Networks. 74-85 - Marco E. G. V. Cattaneo:
Conditional Probability Estimation. 86-97 - Eunice Yuh-Jie Chen, Arthur Choi, Adnan Darwiche:
On Pruning with the MDL Score. 98-109 - Fábio Gagliardi Cozman, Denis Deratani Mauá:
Probabilistic Graphical Models Specified by Probabilistic Logic Programs: Semantics and Complexity. 110-122 - Jasper De Bock:
Reintroducing Credal Networks under Epistemic Irrelevance. 123-135 - Eugene Dementiev, Norman E. Fenton:
Bayesian Torrent Classification by File Name and Size Only. 136-146 - Nicola Di Mauro, Antonio Vergari, Floriana Esposito:
Multi-Label Classification with Cutset Networks. 147-158 - Eva Endres, Thomas Augustin:
Statistical Matching of Discrete Data by Bayesian Networks. 159-170 - Nourhene Ettouzi, Philippe Leray, Montassar Ben Messaoud:
An Exact Approach to Learning Probabilistic Relational Model. 171-182 - Maxime Gasse, Alex Aussem:
Identifying the irreducible disjoint factors of a multivariate probability distribution. 183-194 - Michael Glodek, Georg Layher, Heiko Neumann, Susanne Biundo, Günther Palm:
On Stacking Probabilistic Temporal Models with Bidirectional Information Flow. 195-206 - Christiane Görgen, Jim Q. Smith:
A Differential Approach to Causality in Staged Trees. 207-215 - Antti Hyttinen, Sergey M. Plis, Matti Järvisalo, Frederick Eberhardt, David Danks:
Causal Discovery from Subsampled Time Series Data by Constraint Optimization. 216-227 - Priyank Jaini, Abdullah Rashwan, Han Zhao, Yue Liu, Ershad Banijamali, Zhitang Chen, Pascal Poupart:
Online Algorithms for Sum-Product Networks with Continuous Variables. 228-239 - Kiran Karra, Lamine Mili:
Hybrid Copula Bayesian Networks. 240-251 - Jidapa Kraisangka, Marek J. Druzdzel:
Making Large Cox's Proportional Hazard Models Tractable in Bayesian Networks. 252-263 - Johan Kwisthout:
The Parameterized Complexity of Approximate Inference in Bayesian Networks. 264-274 - Evangelia Kyrimi, William Marsh:
A Progressive Explanation of Inference in 'Hybrid' Bayesian Networks for Supporting Clinical Decision Making. 275-286 - Manxia Liu, Arjen Hommersom, Maarten van der Heijden, Peter J. F. Lucas:
Learning Parameters of Hybrid Time Bayesian Networks. 287-298 - Daniel Malinsky, Peter Spirtes:
Estimating Causal Effects with Ancestral Graph Markov Models. 299-309 - Peter Marx, András Millinghoffer, Gabriella Juhász, Peter Antal:
Joint Bayesian Modelling of Internal Dependencies and Relevant Multimorbidities of a Heterogeneous Disease. 310-320 - Andrés R. Masegosa, Ana M. Martínez, Helge Langseth, Thomas D. Nielsen, Antonio Salmerón, Darío Ramos-López, Anders L. Madsen:
d-VMP: Distributed Variational Message Passing. 321-332 - Denis Deratani Mauá, Fábio Gagliardi Cozman:
The Effect of Combination Functions on the Complexity of Relational Bayesian Networks. 333-344 - Mazen Melibari, Pascal Poupart, Prashant Doshi, George Trimponias:
Dynamic Sum Product Networks for Tractable Inference on Sequence Data. 345-355 - Carlos Morales, Serafín Moral:
Regression Methods Applied to Flight Variables for Situational Awareness Estimation Using Dynamic Bayesian Networks. 356-367 - Juan Miguel Ogarrio, Peter Spirtes, Joe Ramsey:
A Hybrid Causal Search Algorithm for Latent Variable Models. 368-379 - Pekka Parviainen, Samuel Kaski:
Bayesian Networks for Variable Groups. 380-391 - José M. Peña:
Learning Acyclic Directed Mixed Graphs from Observations and Interventions. 392-402 - Martin Plajner, Jirí Vomlel:
Student Skill Models in Adaptive Testing. 403-414 - Darío Ramos-López, Antonio Salmerón, Rafael Rumí, Ana M. Martínez, Thomas D. Nielsen, Andrés R. Masegosa, Helge Langseth, Anders L. Madsen:
Scalable MAP inference in Bayesian networks based on a Map-Reduce approach. 415-425 - Silja Renooij:
Evidence Evaluation: a Study of Likelihoods and Independence. 426-437 - Marco Scutari:
An Empirical-Bayes Score for Discrete Bayesian Networks. 438-448 - Konstantinos Sechidis, Matthew Sperrin, Emily Petherick, Gavin Brown:
Estimating Mutual Information in Under-Reported Variables. 449-461 - Ross D. Shachter:
Decisions and Dependence in Influence Diagrams. 462-473 - Ivar Simonsson, Petter Mostad:
Exact Inference on Conditional Linear Γ-Gaussian Bayesian Networks. 474-486 - Elena Sokolova, Martine Hoogman, Perry Groot, Tom Claassen, Tom Heskes:
Computing Lower and Upper Bounds on the Probability of Causal Statements. 487-498 - Milan Studený, James Cussens:
The Chordal Graph Polytope for Learning Decomposable Models. 499-510 - Priya Krishnan Sundararajan, Ole J. Mengshoel:
A Genetic Algorithm for Learning Parameters in Bayesian Networks using Expectation Maximization. 511-522 - Yi Tan, Prakash P. Shenoy, Moses W. Chan, Paul M. Romberg:
On Construction of Hybrid Logistic Regression-Naïve Bayes Model for Classification. 523-534 - Yang Xiang, Qian Jiang:
Compressing Bayes Net CPTs with Persistent Leaky Causes. 535-546
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