1
2
Assuntos:
“...Deep Reinforcement Learning...”
Jaguar: a hierarchical deep reinforcement learning approach with transfer learning for StarCraft II
Dissertação
3
“...Inducing models from a dataset is an inverse problem and usually it is ill-posed. To turn this into...”
Regularização de extreme Learning Machines: uma abordagem com matrizes de afinidade
Tese
4
5
Assuntos:
“...Learning of robust structures...”
Structure learning of Bayesian networks via data perturbation
Tese
6
Assuntos:
“...Learning design...”
Learning design aplicado ao projeto de unidades de aprendizagem
Tese
9
“..., covering distinct aspects of the problem and distinct strategies. Despite the large number of existent...”
An unsupervised approach based on self-learning for the combination of sentiment analysis methods
Dissertação
10
“..., supporting a comprehensible analysis according to the problem and the dataset. Each visualization provides...”
Uncovering discrimination generated by different machine learning methods using data visualization
Dissertação
11
Assuntos:
“...Deep Learning...”
Aprendizagem semissupervisionada por meio de técnicas de Deep Learning e de Teoria da Informação
Tese
12
“... formulation of the problem and using it to elaborate theoretical proofs. Another approach consists...”
Analysis of the impacts of label dependence in multi-label learning
Tese
13
14
“.... In addition, in order to validate the problem and gather more information about the impact of gender...”
A supervised learning approach to detect gender stereotype in online educational technologies
Dissertação
15
Assuntos:
“...Machine learning...”
Per-instance algorithm configuration: from meta-learning to multi-objective decomposition
Tese
16
Assuntos:
“...[en] MACHINE LEARNING...”
[en] ASSESSING THE BENEFITS OF MLOPS FOR SUPERVISED ONLINE REGRESSION MACHINE LEARNING
Tese
17
Assuntos:
“...Meta-learning...”
A meta-learning approach for auto-selection and auto-configuration of proximity graphs
Dissertação
18
19
Assuntos:
“...[en] AUTOMATIC LEARNING...”
[en] HIERARQUICAL NEURO-FUZZY MODELS BASED ON REINFORCEMENT LEARNING FOR INTELLIGENT AGENTS
Tese
20
Assuntos:
“...Deep learning...”
Deep learning approach for trajectory user-linking in multidimensional and imbalanced datasets
Tese