Cassio P. de Campos

David Ricardo Montalvan Hernandez

Carlos Dias Maciel

Appl. Intell., March, 2024

Beyond tree-shaped credal probabilistic circuits.

[BibT_eX]

[DOI]

Int. J. Approx. Reason., 2024

Extended papers from the 11th International Symposium on Imprecise Probabilities: Theories and Applications.

[BibT_eX]

[DOI]

Jasper De Bock

Gert De Cooman

Int. J. Approx. Reason., 2024

What is the Relationship between Tensor Factorizations and Circuits (and How Can We Exploit it)?

[BibT_eX]

[DOI]

CoRR, 2024

Nerva: a Truly Sparse Implementation of Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2024

Scaling Continuous Latent Variable Models as Probabilistic Integral Circuits.

[BibT_eX]

[DOI]

CoRR, 2024

Soft Learning Probabilistic Circuits.

[BibT_eX]

[DOI]

Soroush Ghandi

Benjamin Quost

CoRR, 2024

Probabilistic Circuits with Constraints via Convex Optimization.

[BibT_eX]

[DOI]

Soroush Ghandi

Benjamin Quost

David Ricardo Montalvan Hernandez

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

Dempster-Shafer Credal Probabilistic Circuits.

[BibT_eX]

[DOI]

Thomas Krak

Proceedings of the Belief Functions: Theory and Applications, 2024

Probabilistic Integral Circuits.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Probabilistic Multi-Dimensional Classification.

[BibT_eX]

[DOI]

Vu-Linh Nguyen

Yang Yang

David Ricardo Montalvan Hernandez

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Portfolio Optimization via Credal Probabilistic Circuits.

[BibT_eX]

[DOI]

Proceedings of the 4th ACM International Conference on AI in Finance, 2023

Continuous Mixtures of Tractable Probabilistic Models.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

High-Value Token-Blocking: Efficient Blocking Method for Record Linkage.

[BibT_eX]

[DOI]

Kevin O'Hare

Anna Jurek-Loughrey

ACM Trans. Knowl. Discov. Data, 2022

2021

Special Issue on Robustness in Probabilistic Graphical Models.

[BibT_eX]

[DOI]

Int. J. Approx. Reason., 2021

Bayesian Kernelised Test of (In)dependence with Mixed-type Variables.

[BibT_eX]

[DOI]

CoRR, 2021

Bayesian Independence Test with Mixed-type Variables.

[BibT_eX]

[DOI]

Proceedings of the 8th IEEE International Conference on Data Science and Advanced Analytics, 2021

2020

A structured view on weighted counting with relations to counting, quantum computation and applications.

[BibT_eX]

[DOI]

Georgios Stamoulis

Dennis Weyland

Inf. Comput., 2020

Towards Robust Classification with Deep Generative Forests.

[BibT_eX]

[DOI]

Alvaro H. C. Correia

Robert Peharz

CoRR, 2020

Almost No News on the Complexity of MAP in Bayesian Networks.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Probabilistic Graphical Models, 2020

Joints in Random Forests.

[BibT_eX]

[DOI]

Alvaro H. C. Correia

Robert Peharz

Alvaro Henrique Chaim Correia

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

On Pruning for Score-Based Bayesian Network Structure Learning.

[BibT_eX]

[DOI]

James Cussens

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

A hierarchy of sum-product networks using robustness.

[BibT_eX]

[DOI]

Jesús Martínez del Rincón

Int. J. Approx. Reason., 2019

An unsupervised blocking technique for more efficient record linkage.

[BibT_eX]

[DOI]

Kevin O'Hare

Anna Jurek-Loughrey

Data Knowl. Eng., 2019

Towards Scalable and Robust Sum-Product Networks.

[BibT_eX]

[DOI]

Alvaro H. C. Correia

Proceedings of the Scalable Uncertainty Management - 13th International Conference, 2019

Robustness in Sum-Product Networks with Continuous and Categorical Data.

[BibT_eX]

[DOI]

Rob Wit

Jesús Martínez del Rincón

Proceedings of the International Symposium on Imprecise Probabilities: Theories and Applications, 2019

An Experimental Study of Prior Dependence in Bayesian Network Structure Learning.

[BibT_eX]

[DOI]

Alvaro Henrique Chaim Correia

Linda C. van der Gaag

Proceedings of the International Symposium on Imprecise Probabilities: Theories and Applications, 2019

2018

Approximate structure learning for large Bayesian networks.

[BibT_eX]

[DOI]

Mauro Scanagatta

Giorgio Corani

Mach. Learn., 2018

A new technique of selecting an optimal blocking method for better record linkage.

[BibT_eX]

[DOI]

Kevin O'Hare

Anna Jurek

Inf. Syst., 2018

Robustifying sum-product networks.

[BibT_eX]

[DOI]

Katja Poppenhaeger

Int. J. Approx. Reason., 2018

Entropy-based pruning for learning Bayesian networks using BIC.

[BibT_eX]

[DOI]

Artif. Intell., 2018

Cascading Sum-Product Networks using Robustness.

[BibT_eX]

[DOI]

Jesús Martínez del Rincón

Proceedings of the International Conference on Probabilistic Graphical Models, 2018

2017

Joint Analysis of Multiple Algorithms and Performance Measures.

[BibT_eX]

[DOI]

New Gener. Comput., 2017

Efficient learning of Bayesian networks with bounded tree-width.

[BibT_eX]

[DOI]

Siqi Nie

Int. J. Approx. Reason., 2017

Introduction to the special issue on statistical and computational methods for genomics and integrative genomics.

[BibT_eX]

[DOI]

Paola M. V. Rancoita

Int. J. Approx. Reason., 2017

Approximation Complexity of Maximum A Posteriori Inference in Sum-Product Networks.

[BibT_eX]

[DOI]

CoRR, 2017

Approximation Complexity of Maximum A Posteriori Inference in Sum-Product Networks.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Credal Sum-Product Networks.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Symposium on Imprecise Probability: Theories and Applications, 2017

Learning Bayesian Networks with Incomplete Data by Augmentation.

[BibT_eX]

[DOI]

Tameem Adel

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Hidden Markov models with set-valued parameters.

[BibT_eX]

[DOI]

Neurocomputing, 2016

Learning extended tree augmented naive structures.

[BibT_eX]

[DOI]

Int. J. Approx. Reason., 2016

Ordering Quantiles through Confidence Statements.

[BibT_eX]

[DOI]

Carlos Alberto De Bragança Pereira

Paola M. V. Rancoita

Adriano Polpo

Entropy, 2016

Bayesian Dependence Tests for Continuous, Binary and Mixed Continuous-Binary Variables.

[BibT_eX]

[DOI]

Entropy, 2016

Bayesian network data imputation with application to survival tree analysis.

[BibT_eX]

[DOI]

Comput. Stat. Data Anal., 2016

Learning Bounded Treewidth Bayesian Networks with Thousands of Variables.

[BibT_eX]

[DOI]

CoRR, 2016

Learning Bayesian Networks without Assuming Missing at Random.

[BibT_eX]

[DOI]

Tameem Adel

CoRR, 2016

Learning Treewidth-Bounded Bayesian Networks with Thousands of Variables.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Learning Bayesian Networks with Bounded Tree-width via Guided Search.

[BibT_eX]

[DOI]

Siqi Nie

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Approximate credal network updating by linear programming with applications to decision making.

[BibT_eX]

[DOI]

Int. J. Approx. Reason., 2015

Averaged Extended Tree Augmented Naive Classifier.

[BibT_eX]

[DOI]

Aaron Meehan

Entropy, 2015

Imprecision in Machine Learning and AI.

[BibT_eX]

[DOI]

IEEE Intell. Informatics Bull., 2015

Learning Bayesian Networks with Thousands of Variables.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Statistical Tests for Joint Analysis of Performance Measures.

[BibT_eX]

[DOI]

Proceedings of the Advanced Methodologies for Bayesian Networks, 2015

The Complexity of MAP Inference in Bayesian Networks Specified Through Logical Languages.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

Learning Bounded Tree-Width Bayesian Networks via Sampling.

[BibT_eX]

[DOI]

Siqi Nie

Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2015

2014

Probabilistic Inference in Credal Networks: New Complexity Results.

[BibT_eX]

[DOI]

J. Artif. Intell. Res., 2014

Kuznetsov independence for interval-valued expectations and sets of probability distributions: Properties and algorithms.

[BibT_eX]

[DOI]

Int. J. Approx. Reason., 2014

Transform both sides model: A parametric approach.

[BibT_eX]

[DOI]

Comput. Stat. Data Anal., 2014

Min-BDeu and Max-BDeu Scores for Learning Bayesian Networks.

[BibT_eX]

[DOI]

Mauro Scanagatta

Proceedings of the Probabilistic Graphical Models - 7th European Workshop, 2014

Extended Tree Augmented Naive Classifier.

[BibT_eX]

[DOI]

Proceedings of the Probabilistic Graphical Models - 7th European Workshop, 2014

Advances in Learning Bayesian Networks of Bounded Treewidth.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Global Sensitivity Analysis for MAP Inference in Graphical Models.

[BibT_eX]

[DOI]

Jasper De Bock

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

The Computational Complexity of Stochastic Optimization.

[BibT_eX]

[DOI]

Georgios Stamoulis

Dennis Weyland

Proceedings of the Combinatorial Optimization - Third International Symposium, 2014

Algorithms for Hidden Markov Models with Imprecisely Specified Parameters.

[BibT_eX]

[DOI]

Proceedings of the 2014 Brazilian Conference on Intelligent Systems, 2014

2013

A Structured View on Weighted Counting with Relations to Quantum Computation and Applications.

[BibT_eX]

[DOI]

Georgios Stamoulis

Dennis Weyland

Electron. Colloquium Comput. Complex., 2013

On the complexity of solving polytree-shaped limited memory influence diagrams with binary variables.

[BibT_eX]

[DOI]

Artif. Intell., 2013

On the Complexity of Strong and Epistemic Credal Networks.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

Approximating Credal Network Inferences by Linear Programming.

[BibT_eX]

[DOI]

Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2013

Complexity of Inferences in Polytree-shaped Semi-Qualitative Probabilistic Networks.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence, 2013

2012

Solving Limited Memory Influence Diagrams.

[BibT_eX]

[DOI]

J. Artif. Intell. Res., 2012

Updating credal networks is approximable in polynomial time.

[BibT_eX]

[DOI]

Int. J. Approx. Reason., 2012

Propositional and Relational Bayesian Networks Associated with Imprecise and Qualitative Probabilistic Assesments

[BibT_eX]

[DOI]

Jaime Shinsuke Ide

CoRR, 2012

The Complexity of Approximately Solving Influence Diagrams.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

Anytime Marginal MAP Inference.

[BibT_eX]

[DOI]

Proceedings of the 29th International Conference on Machine Learning, 2012

2011

Integração de evidências em redes credais e a regra de Jeffrey.

[BibT_eX]

[DOI]

Alaine Margarete Guimarães

RITA, 2011

Efficient Structure Learning of Bayesian Networks using Constraints.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2011

Improving parameter learning of Bayesian nets from incomplete data

[BibT_eX]

[DOI]

Giorgio Corani

CoRR, 2011

Solving Decision Problems with Limited Information.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Inference with Multinomial Data: Why to Weaken the Prior Strength.

[BibT_eX]

[DOI]

Proceedings of the IJCAI 2011, 2011

New Complexity Results for MAP in Bayesian Networks.

[BibT_eX]

[DOI]

Proceedings of the IJCAI 2011, 2011

Bayesian Networks and the Imprecise Dirichlet Model Applied to Recognition Problems.

[BibT_eX]

[DOI]

Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2011

2010

A tree augmented classifier based on Extreme Imprecise Dirichlet Model.

[BibT_eX]

[DOI]

Giorgio Corani

Int. J. Approx. Reason., 2010

Generalized loopy 2U: A new algorithm for approximate inference in credal networks.

[BibT_eX]

[DOI]

Int. J. Approx. Reason., 2010

New Results for the MAP Problem in Bayesian Networks

[BibT_eX]

[DOI]

CoRR, 2010

An Improved Structural EM to Learn Dynamic Bayesian Nets.

[BibT_eX]

[DOI]

Zhi Zeng

Proceedings of the 20th International Conference on Pattern Recognition, 2010

Properties of Bayesian Dirichlet Scores to Learn Bayesian Network Structures.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010

2009

Assembling a consistent set of sentences in relational probabilistic logic with stochastic independence.

[BibT_eX]

[DOI]

José Eduardo Ochoa Luna

J. Appl. Log., 2009

Structure learning of Bayesian networks using constraints.

[BibT_eX]

[DOI]

Zhi Zeng

Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Inference from Multinomial Data Based on a MLE-Dominance Criterion.

[BibT_eX]

[DOI]

Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2009

2008

Probabilistic logic with independence.

[BibT_eX]

[DOI]

Int. J. Approx. Reason., 2008

Strategy Selection in Influence Diagrams using Imprecise Probabilities.

[BibT_eX]

[DOI]

Proceedings of the UAI 2008, 2008

Improving Bayesian Network parameter learning using constraints.

[BibT_eX]

[DOI]

Proceedings of the 19th International Conference on Pattern Recognition (ICPR 2008), 2008

Constrained Maximum Likelihood Learning of Bayesian Networks for Facial Action Recognition.

[BibT_eX]

[DOI]

Yan Tong

Proceedings of the Computer Vision, 2008

2007

Computing lower and upper expectations under epistemic independence.

[BibT_eX]

[DOI]

Int. J. Approx. Reason., 2007

2006

Probabilistic Logic with Strong Independence.

[BibT_eX]

[DOI]

Proceedings of the Advances in Artificial Intelligence, 2006

2005

Belief Updating and Learning in Semi-Qualitative Probabilistic Networks.

[BibT_eX]

[DOI]

Proceedings of the UAI '05, 2005

The Inferential Complexity of Bayesian and Credal Networks.

[BibT_eX]

[DOI]

Proceedings of the IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005

2004

Propositional and Relational Bayesian Networks Associated with Imprecise and Qualitat.

[BibT_eX]

[DOI]

Jaime Shinsuke Ide