Relational learning
Composition of Sentence Embeddings: Lessons from Statistical Relational Learning
... tical Relational Learning (SRL) whose goal is to predict relations between entities (typically from knowledge base ...textual relational problems, showing that they are more expressive, and can ...
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Determining the Number of Latent Factors in Statistical Multi-Relational Learning
... Statistical relational learning is primarily concerned with learning from relational data sets, and solving tasks such as predicting whether two entities are related (link prediction), ...
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kLogNLP: Graph Kernel–based Relational Learning of Natural Language
... additional relational features in a declarative way. The resulting relational represen- tation then serves as input for kLog, and thus re- sults in a full relational learning pipeline for ...
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Statistical Relational Learning for Proteomics: Function, Interactions and Evolution
... complex learning settings and corresponding learning ...statistical relational learning approach [228] capable of learn- ing weighted combinations of relational rules discriminating ...
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Relational Learning as Search in a Critical Region
... Previous experiments (Botta, Giordana, and Saitta, 1999; Botta, Giordana, Saitta, and Sebag, 2000; Giordana and Saitta, 2000) have shown the presence of a phase transition in the covering test, both in artificial and ...
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A Statistical Relational Learning Approach to Identifying Evidence Based Medicine Categories
... statistical relational learning systems (Getoor and Taskar, 2007; De Raedt et ...statistical learning theory, and 2) it employs a Prolog like language for defining and us- ing background ...
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Neural Relational Learning Through Semi-Propositionalization of Bottom Clauses
... Relational learning can be described as the task of learning first-order logic rules from ...machine learning applica- tions, ...efficient relational learning, by be- ing able to ...
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Introducing DRAIL – a Step Towards Declarative Deep Relational Learning
... deep learning allow these meth- ods to successfully learn such mappings over very high dimensional latent features space (Duchi et ...specific learning architecture used for learning ...Deep ...
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Meta Relational Learning for Few Shot Link Prediction in Knowledge Graphs
... ing, learning a matching metric by considering both learned embeddings and one-hop graph struc- tures, while we try to accomplish few-shot link prediction from another perspective based on the intuition that the ...
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Relational Learning of Pattern Match Rules for Information Extraction
... Given the recent success of empirical or corpus- based approaches in other areas of natu- ral language processing, machine learning has the potential to significantly aid the development[r] ...
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The effect of relational learning on the development of reversal and nonreversal shifts.
... Stage III: B i - d imensional l e a r n i n g . On the day after the relational task was completed, _S was presented with the following problem. Using the same d i s c rimination apparatus and correction ...
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Adaptive Convolution for Multi Relational Learning
... tations with its filters adaptively constructed from relation representations. Such adaptive convolution will model the interactions between the two types of input not only more naturally but also more ef- fectively. ...
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Statistical and Relational Learning for Understanding Enzyme Function
... for the task-specific models, favouring parameter sharing among related tasks. These models allow for a great flexibility in modelling different levels of tasks relatedness. Bakker and Heskes [5] for instance, generalise ...
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Relational Matching to Sample Concept Learning in Children
... identical relational matching-to-sample concept learning in children, in which five students of kindergarten aged 7-8 were concurrently trained with two-choice relational matching-to-sample (RMTS) ...
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A Comparative Study Of Multi-Relational Decision Tree Learning Algorithm
... a relational database, these are often viewed conveniently as heterogeneous data sources as if they are a collection of relations [1] which are then utilized for the purpose of extracting, inferring and organizing ...
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Learning Relational Features with Backward Random Walks
... or relational learning systems, PRA is limited to learning from binary predicates, and applies random-walk semantics to its ...The relational feature construction problem (or ...
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Exploration in Relational Domains for Model-based Reinforcement Learning
... a relational learning algorithm of noisy indeterministic deictic (NID) rules (Pasula et ...stochastic relational rule-based model from ...learned relational model to a grounded dynamic ...
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Who can you count on? The relational dimension of new teacher learning
... informal learning. According to Gorard et al. (1999), informal learning has been neglected in official policy statements and standards in the field of lifelong learning too, and also in the narrow ...
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Inquiry as relational practice: Thinking relationally about the practice of teaching and learning
... of learning community has become ...for learning from reflection on experience (Reynolds, 2000; Reynolds and Trehan, ...the learning task (Simpson, French, and Vince, ...
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Leveraging Lexical Resources for Learning Entity Embeddings in Multi Relational Data
... in learning vector-space em- beddings for multi-relational data has fo- cused on combining relational information derived from knowledge bases with dis- tributional information derived from large ...
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