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Constrained Optimization with Qualitative Preferences
In our second solution, we extend the Lexicographic Preference Tree (LP-tree) to a set of constraints.
Exact Learning of Qualitative Constraint Networks from Membership Queries
A Qualitative Constraint Network (QCN) is a constraint graph for representing problems under qualitative temporal and spatial relations, among others.
An Ontology-Based Information Extraction System for Residential Land Use Suitability Analysis
A case study has been conducted where the output from LUSA OBIE is applied to help produce a suitability map for the City of Regina, Saskatchewan, to assist in the identification of suitable areas for residential development.
Optimizing Neural Network Weights using Nature-Inspired Algorithms
This study aims to optimize Deep Feedforward Neural Networks (DFNNs) training using nature-inspired optimization algorithms, such as PSO, MTO, and its variant called MTOCL.
Effect of Word Embedding Models on Hate and Offensive Speech Detection
Next, based on a dataset of Arabic hate and offensive speech, for each detection task, we train several neural network classifiers using the pre-trained word embedding models.
The Complexity of Learning Acyclic Conditional Preference Networks
To assess the optimality of learning algorithms as well as to better understand the combinatorial structure of classes of CP-nets, it is helpful to calculate certain learning-theoretic information complexity parameters.
