| Word embeddings-based transfer learning for boosted relational dependency networks.   | MLJ | 2024 | 0 | 
        
        
            | Select First, Transfer Later: Choosing Proper Datasets for Statistical Relational Transfer Learning.   | ILP | 2023 | 0 | 
        
        
            | Sentiment analysis in tweets: an assessment study from classical to modern word representation models.   | DMKD | 2023 | 0 | 
        
        
            | Combining Word Embeddings-Based Similarity Measures for Transfer Learning Across Relational Domains.   | ILP | 2022 | 0 | 
        
        
            | Screening for Depressed Individuals by Using Multimodal Social Media Data.   | AAAI | 2021 | 1 | 
        
        
            | Transfer Learning for Boosted Relational Dependency Networks Through Genetic Algorithm.   | ILP | 2021 | 2 | 
        
        
            | Mapping Across Relational Domains for Transfer Learning with Word Embeddings-Based Similarity.   | ILP | 2021 | 2 | 
        
        
            | Transfer learning by mapping and revising boosted relational dependency networks.   | MLJ | 2020 | 0 | 
        
        
            | Online probabilistic theory revision from examples with ProPPR.   | MLJ | 2019 | 6 | 
        
        
            | Lightweight Neural Programming: The GRPU.   | ICANN | 2018 | 0 | 
        
        
            | Towards Safer (Smart) Cities: Discovering Urban Crime Patterns Using Logic-based Relational Machine Learning.   | IJCNN | 2018 | 6 | 
        
        
            | On the use of stochastic local search techniques to revise first-order logic theories from examples.   | MLJ | 2017 | 8 | 
        
        
            | Chess Revision: Acquiring the Rules of Chess Variants through FOL Theory Revision from Examples.   | ILP | 2009 | 17 | 
        
        
            | Using the bottom clause and mode declarations in FOL theory revision from examples.   | MLJ | 2009 | 13 | 
        
        
            | Using the Bottom Clause and Mode Declarations on FOL Theory Revision from Examples.   | ILP | 2008 | 18 | 
        
        
            | Revising First-Order Logic Theories from Examples Through Stochastic Local Search.   | ILP | 2007 | 11 | 
        
        
            | ILP Through Propositionalization and Stochastic k-Term DNF Learning.   | ILP | 2006 | 0 | 
        
        
            | Probabilistic First-Order Theory Revision from Examples.   | ILP | 2005 | 19 |