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Proceedings of Machine Learning Research

Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research Proceedings of Machine Learning Research
Proceedings of Machine Learning Research
PMLR · 2026-06-02 · via Proceedings of Machine Learning Research

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Volume 52: Conference on Probabilistic Graphical Models, 6-9 September 2016, Lugano, Switzerland

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Editors: Alessandro Antonucci, Giorgio Corani, Cassio Polpo Campos

[bib][citeproc]

Contents:

  • Preface
  • Accepted Papers

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Preface

Proceedings of the Eighth International Conference on Probabilistic Graphical Models

; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:i-iv

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Accepted Papers

Regime Aware Learning

Marcus Bendtsen; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:1-12

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Learning Tractable Multidimensional Bayesian Network Classifiers

Marco Benjumeda, Concha Bielza, Pedro Larrañaga; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:13-24

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Bayesian Matrix Factorization with Non-Random Missing Data using Informative Gaussian Process Priors and Soft Evidences

Bence Bolgár, Péter Antal; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:25-36

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Bayesian Networks: a Combined Tuning Heuristic

Janneke H. Bolt; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:37-49

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Learning Complex Uncertain States Changes via Asymmetric Hidden Markov Models: an Industrial Case

Marcos L.P. Bueno, Arjen Hommersom, Peter J.F. Lucas, Sicco Verwer, Alexis Linard; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:50-61

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On Bayesian Network Inference with Simple Propagation

Cory J. Butz, Jhonatan S. Oliveira, André E. dos Santos, Anders L. Madsen; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:62-73

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Relevant Path Separation: A Faster Method for Testing Independencies in Bayesian Networks

Cory J. Butz, André E. dos Santos, Jhonatan S. Oliveira; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:74-85

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Conditional Probability Estimation

Marco E. G. V. Cattaneo; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:86-97

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On Pruning with the MDL Score

Eunice Yuh-Jie Chen, Arthur Choi, Adnan Darwiche; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:98-109

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Probabilistic Graphical Models Specified by Probabilistic Logic Programs: Semantics and Complexity

Fabio Gagliardi Cozman, Denis Deratani Mauá; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:110-122

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Reintroducing Credal Networks under Epistemic Irrelevance

Jasper De Bock; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:123-135

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Bayesian Torrent Classification by File Name and Size Only

Eugene Dementiev, Norman Fenton; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:136-146

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Multi-Label Classification with Cutset Networks

Nicola Di Mauro, Antonio Vergari, Floriana Esposito; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:147-158

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Statistical Matching of Discrete Data by Bayesian Networks

Eva Endres, Thomas Augustin; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:159-170

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An Exact Approach to Learning Probabilistic Relational Model

Nourhene Ettouzi, Philippe Leray, Montassar Ben Messaoud; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:171-182

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Identifying the irreducible disjoint factors of a multivariate probability distribution

Maxime Gasse, Alex Aussem; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:183-194

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On Stacking Probabilistic Temporal Models with Bidirectional Information Flow

Thomas Geier, Michael Glodek, Georg Layher, Heiko Neumann, Susanne Biundo, Günther Palm; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:195-206

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A Differential Approach to Causality in Staged Trees

Christiane Görgen, Jim Q. Smith; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:207-215

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Causal Discovery from Subsampled Time Series Data by Constraint Optimization

Antti Hyttinen, Sergey Plis, Matti Järvisalo, Frederick Eberhardt, David Danks; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:216-227

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Online Algorithms for Sum-Product Networks with Continuous Variables

Priyank Jaini, Abdullah Rashwan, Han Zhao, Yue Liu, Ershad Banijamali, Zhitang Chen, Pascal Poupart; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:228-239

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Hybrid Copula Bayesian Networks

Kiran Karra, Lamine Mili; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:240-251

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Making Large Cox’s Proportional Hazard Models Tractable in Bayesian Networks

Jidapa Kraisangka, Marek J. Druzdzel; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:252-263

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The Parameterized Complexity of Approximate Inference in Bayesian Networks

Johan Kwisthout; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:264-274

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A Progressive Explanation of Inference in ‘Hybrid’ Bayesian Networks for Supporting Clinical Decision Making

Evangelia Kyrimi, William Marsh; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:275-286

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Learning Parameters of Hybrid Time Bayesian Networks

Manxia Liu, Arjen Hommersom, Maarten van der Heijden, Peter J.F. Lucas; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:287-298

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Estimating Causal Effects with Ancestral Graph Markov Models

Daniel Malinsky, Peter Spirtes; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:299-309

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Joint Bayesian Modelling of Internal Dependencies and Relevant Multimorbidities of a Heterogeneous Disease

Péter Marx, András Millinghoffer, Gabriella Juhász, Péter Antal; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:310-320

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d-VMP: Distributed Variational Message Passing

Andrés R. Masegosa, Ana M. Martı́nez, Helge Langseth, Thomas D. Nielsen, Antonio Salmerón, Darío Ramos-López, Anders L. Madsen; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:321-332

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The Effect of Combination Functions on the Complexity of Relational Bayesian Networks

Denis Deratani Mauá, Fabio Gagliardi Cozman; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:333-344

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Dynamic Sum Product Networks for Tractable Inference on Sequence Data

Mazen Melibari, Pascal Poupart, Prashant Doshi, George Trimponias; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:345-355

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Regression Methods Applied to Flight Variables for Situational Awareness Estimation Using Dynamic Bayesian Networks

Carlos Morales, Serafín Moral; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:356-367

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A Hybrid Causal Search Algorithm for Latent Variable Models

Juan Miguel Ogarrio, Peter Spirtes, Joe Ramsey; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:368-379

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Bayesian Networks for Variable Groups

Pekka Parviainen, Samuel Kaski; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:380-391

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Learning Acyclic Directed Mixed Graphs from Observations and Interventions

Jose M. Peña; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:392-402

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Student Skill Models in Adaptive Testing

Martin Plajner, Jiří Vomlel; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:403-414

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Scalable MAP inference in Bayesian networks based on a Map-Reduce approach

Darı́o Ramos-López, Antonio Salmerón, Rafel Rumı́, Ana M. Martı́nez, Thomas D. Nielsen, Andrés R. Masegosa, Helge Langseth, Anders L. Madsen; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:415-425

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Evidence Evaluation: a Study of Likelihoods and Independence

Silja Renooij; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:426-437

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An Empirical-Bayes Score for Discrete Bayesian Networks

Marco Scutari; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:438-448

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Estimating Mutual Information in Under-Reported Variables

Konstantinos Sechidis, Matthew Sperrin, Emily Petherick, Gavin Brown; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:449-461

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Decisions and Dependence in Influence Diagrams

Ross D. Shachter; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:462-473

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Exact Inference on Conditional Linear Γ-Gaussian Bayesian Networks

Ivar Simonsson, Petter Mostad; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:474-486

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Computing Lower and Upper Bounds on the Probability of Causal Statements

Elena Sokolova, Martine Hoogman, Perry Groot, Tom Claassen, Tom Heskes; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:487-498

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The Chordal Graph Polytope for Learning Decomposable Models

Milan Studený, James Cussens; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:499-510

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A Genetic Algorithm for Learning Parameters in Bayesian Networks using Expectation Maximization

Priya Krishnan Sundararajan, Ole J. Mengshoel; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:511-522

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On Construction of Hybrid Logistic Regression-Naïve Bayes Model for Classification

Yi Tan, Prakash P. Shenoy, Moses W. Chan, Paul M. Romberg; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:523-534

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Compressing Bayes Net CPTs with Persistent Leaky Causes

Yang Xiang, Qian Jiang; Proceedings of the Eighth International Conference on Probabilistic Graphical Models, PMLR 52:535-546

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此内容由惯性聚合(RSS阅读器)自动聚合整理，仅供阅读参考。 原文来自 — 版权归原作者所有。