Results 101 to 110 of about 1,061,373 (212)
Learning Class-Level Bayes Nets for Relational Data [PDF]
arXiv, 2008 Many databases store data in relational format, with different types of entities and information about links between the entities. The field of statistical-relational learning (SRL) has developed a number of new statistical models for such data. In this paper we focus on learning class-level or first-order dependencies, which model the general database
arxiv
RelEx: A Model-Agnostic Relational Model Explainer [PDF]
arXiv, 2020 In recent years, considerable progress has been made on improving the interpretability of machine learning models. This is essential, as complex deep learning models with millions of parameters produce state of the art results, but it can be nearly impossible to explain their predictions. While various explainability techniques have achieved impressive
arxiv
Rademacher complexity and spin glasses: A link between the replica and statistical theories of learning [PDF]
Proceedings of The First Mathematical and Scientific Machine
Learning Conference, PMLR 107:27-54, 2020, 2019 Statistical learning theory provides bounds of the generalization gap, using in particular the Vapnik-Chervonenkis dimension and the Rademacher complexity. An alternative approach, mainly studied in the statistical physics literature, is the study of generalization in simple synthetic-data models.
arxiv
The impact of leader self-efficacy on the characteristics of work teams
Intangible Capital, 2017 Purpose: This work focuses on the study of the impact of the Self-Efficacy (SE) of the leader on Innovative Work Behavior (IWB), establishing the influence of contributing factors, such as the Organization Learning Capability (OLC) and Team Member ...
Guillermo Buenaventura-Vera
doaj +1 more source
The effect of lexicalization biases on cross-situational statistical learning of novel verbs
Language and CognitionLanguages vary in the mapping of relational terms onto events. For instance, English motion descriptions favor manner (how something moves) verbs over path (where something move) verbs, whereas those of other languages, like Spanish, show the opposite ...
Nathan R. George +3 more
doaj +1 more source
Accurate prediction of kinase-substrate networks using knowledge graphs.
PLoS Computational Biology, 2020 Phosphorylation of specific substrates by protein kinases is a key control mechanism for vital cell-fate decisions and other cellular processes. However, discovering specific kinase-substrate relationships is time-consuming and often rather serendipitous.
Vít Nováček +14 more
doaj +1 more source
Learning Temporal Structures of Random Patterns [PDF]
arXiv, 2018 A cornerstone of human statistical learning is the ability to extract temporal regularities / patterns from random sequences. Here we present a method of computing pattern time statistics with generating functions for first-order Markov trials and independent Bernoulli trials.
arxiv
Induction of Interpretable Possibilistic Logic Theories from Relational Data
, 2017 The field of Statistical Relational Learning (SRL) is concerned with learning probabilistic models from relational data. Learned SRL models are typically represented using some kind of weighted logical formulas, which make them considerably more ...
Davis, Jesse +2 more
core
INFAD, 2019 Ecopsychology and environmental psychology study the individual-environment relationship, highlighting the benefits that contact with nature can produce in individuals with cognitive, affective, individual and relational benefits.
Rosanna Augello +2 more
doaj +1 more source
Numeric Input Relations for Relational Learning with Applications to Community Structure Analysis
, 2015 Most work in the area of statistical relational learning (SRL) is focussed on discrete data, even though a few approaches for hybrid SRL models have been proposed that combine numerical and discrete variables.
Jaeger, Manfred, Jiang, Jiuchuan
core