Denis Deratani Mauá

Latest

• A New Benchmark for Automatic Essay Scoring in Portuguese
• Specifying credal sets with probabilistic answer set programming
• Assessing Good, Bad and Ugly Arguments Generated by ChatGPT: a New Dataset, its Methodology and Associated Tasks
• Distinct Outcomes in COVID-19 Patients with Positive or Negative RT-PCR Test
• Integrating Question Answering and Text-to-SQL in Portuguese
• Timing to Intubation COVID-19 Patients: Can We Put It Off until Tomorrow?
• Cautious Classification with Data Missing Not at Random using Generative Random Forests
• Efficient algorithms for Risk-Sensitive Markov Decision Processes with limited budget
• Fast And Accurate Learning of Probabilistic Circuits by Random Projections
• Learning Probabilistic Sentential Decision Diagrams under Logic Constraints by Sampling and Averaging
• Complexity results for probabilistic answer set programming
• Efficient Algorithms for Robustness Analysis of Maximum A Posteriori Inference in Selective Sum-Product Networks
• The Joy of Probabilistic Answer Set Programming: Semantics, complexity, expressivity, inference
• Thirty years of credal networks: Specification, algorithms and complexity
• Tractable inference in credal sentential decision diagrams
• Two Reformulation Approaches to Maximum-A-Posteriori Inference in Sum-Product Networks
• Deep Reactive Policies for Planning in Stochastic Nonlinear Domains
• End-To-End Imitation Learning of Lane Following Policies Using Sum-Product Networks
• Exploring the Space of Probabilistic Sentential Decision Diagrams
• Robust Analysis of MAP Inference in Selective Sum-Product Networks
• Speeding up parameter and rule learning for acyclic probabilistic logic programs
• The finite model theory of Bayesian network specifications: Descriptive complexity and zero/one laws
• The Finite Model Theory of Bayesian Networks: Descriptive Complexity
• Advances in Automatically Solving the ENEM
• Robustifying sum-product networks
• The complexity of Bayesian networks specified by propositional and relational languages
• When a Robot Reaches Out for Human Help
• Approximation Complexity of Maximum A Posteriori Inference in Sum-Product Networks
• Approximation Complexity of Maximum A Posteriori Inference in Sum-Product Networks
• Closed-Form Solutions in Learning Probabilistic Logic Programs by Exact Score Maximization
• Credal Sum-Product Networks
• Modeling Markov Decision Processes with Imprecise Probabilities Using Probabilistic Logic Programming
• On the complexity of propositional and relational credal networks
• On the Semantics and Complexity of Probabilistic Logic Programs
• On Using Sum-Product Networks For Multi-Label Classification
• Parameter Learning in ProbLog with Probabilistic Rules
• Speeding-up ProbLog's Parameter Learning
• The Complexity of Inferences and Explanations in Probabilistic Logic Programming
• The Descriptive Complexity of Bayesian Network Specifications
• The effect of combination functions on the complexity of relational Bayesian networks
• University Entrance Exam as a Guiding Test for Artificial Intelligence
• The Complexity of Bayesian Networks Specified by Propositional and Relational Languages
• Better Initialization Heuristics for Order-based Bayesian Network Structure Learning
• Equivalences between maximum a posteriori inference in Bayesian networks and maximum expected utility computation in influence diagrams
• Fast local search methods for solving limited memory influence diagrams
• Hidden Markov models with set-valued parameters
• Improving Acyclic Selection Order-Based Bayesian Network Structure Learning
• Markov Decision Processes Specified by Probabilistic Logic Programming: Representation and Solution
• Probabilistic Graphical Models Specified by Probabilistic Logic Programs: Semantics and Complexity
• The Effect of Combination Functions on the Complexity of Relational Bayesian Networks
• The structure and complexity of credal semantics
• The Well-Founded Semantics of Cyclic Probabilistic Logic Programs
• A Tractable Class of Model Counting Problems
• Bayesian Networks of Bounded Treewith: A Performance Analysis
• Bayesian Networks Specified Using Propositional and Relational Constructs: Combined, Data, and Domain Complexity
• DL-Lite Bayesian Networks: A Tractable Probabilistic Graphical Model
• Initialization Heuristics for Greedy Bayesian Network Structure Learning
• On the Complexity of Propositional and Relational Credal Networks
• Specifying Probabilistic Relational Models with Description Logics
• The Complexity of MAP Inference in Bayesian Networks Specified Through Logical Languages
• The Complexity of Plate Probabilistic Models
• Advances in Learning Bayesian Networks of Bounded Treewidth
• Advances in Learning Bayesian Networks of Bounded Treewidth
• Algorithms for Hidden Markov Models With Imprecisely Specified Parameters
• Equivalences between Maximum a Posteriori Inference in Bayesian Networks and Maximum Expected Utility Computation in Influence Diagrams
• Probabilistic Inference in Credal Networks: New Complexity Results
• Speeding Up k-Neighborhood Local Search in Limited Memory Influence Diagrams
• Trading off Speed and Accuracy in Multilabel Classification
• Algorithms and Complexity Results for Discrete Probabilistic Reasoning Tasks
• An Ensemble of Bayesian Networks for Multilabel Classification
• On the complexity of solving polytree-shaped limited memory influence diagrams with binary variables
• On the Complexity of Strong and Epistemic Credal Networks
• Anytime Marginal MAP Inference
• Evaluating credal classifiers by utility-discounted predictive accuracy
• Solving Limited Memory Influence Diagrams
• The Complexity of Approximately Solving Influence Diagrams
• Updating Credal Networks is Approximable in Polynomial Time
• Solving Limited Memory Influence Diagrams
• A Fully Polynomial Time Approximation Scheme for Updating Credal Networks of Bounded Treewidth and Number of Variable States
• Solving Decision Problems with Limited Information
• Utility-Based Accuracy Measures to Empirically Evaluate Credal Classifiers
• Representing and Classifying User Reviews
• Topic models on the automatic classification of user reviews
• Managing Trust in Virtual Communities with Markov Logic
• Using Social Data to Predict Trust on Web Communities : A Case Study with the Epinions.com Website