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t learning » _ learning (Expandir a busca), b learning (Expandir a busca), shot learning (Expandir a busca)
t learning » _ learning (Expandir a busca), b learning (Expandir a busca), shot learning (Expandir a busca)
1
Assuntos:
“...Algorithms...”
Per-instance algorithm configuration: from meta-learning to multi-objective decomposition
Tese
2
Assuntos:
“...Machine Learning...”
Multi-objective Evolutionary Algorithm Applied to Steel Development
Dissertação
3
Assuntos:
“...Multi-objective optimization...”
A framework for inverse modeling applied to multi-objective evolutionary algorithms
Dissertação
4
5
6
Assuntos:
“...Machine learning...”
Single, multi- and many-objective meta-heuristic algorithms applied to pattern recognition
Tese
7
Assuntos:
“...Evolutionary Algorithm...”
Data-driven multiobjective algorithms : applications in portfolio optimization
Tese
8
9
“...Conclusions in the field of multi-label learning are often drawn from experiments using real...”
Analysis of the impacts of label dependence in multi-label learning
Tese
10
Assuntos:
“...Multi-view Learning...”
Uma abordagem para a pós-seleção de ensembles utilizando conceitos de oráculo e multi-view learning
Tese
11
Assuntos:
“...Multiobjective reinforcement learning...”
Deep Q-Managed: a new framework fror Multi-Objective Deep Reinforcement Learning
Dissertação
12
Assuntos:
“...Multi-agent reinforcement learning...”
A flexible approach for optimal rewards in multi-agent reinforcement learning problems
Tese
13
Assuntos:
“...Multi-objective RL...”
Sample-efficient multi-task and multi-objective reinforcement learning by combining multiple behaviors
Tese
14
Assuntos:
“...[pt] MULTI CLASSE...”
[en] IDENTIFICATION OF PROTEIN SUBCELLULAR LOCALIZATION BY DEEP LEARNING TECHNIQUES
Tese
15
Assuntos:
“...Genetic algorithms...”
Sistemas classificadores evolutivos para problemas multirrótulo
Dissertação
16
Assuntos:
“...evolutionary algorithm...”
Bayesian network quantization method and structural learning
Tese
17
18
19
Assuntos:
“...Representation Learning...”
Image representation learning through genetic quantization
Dissertação
20
Assuntos:
“...[pt] SISTEMAS MULTI-AGENTES...”
[en] HIERARCHICAL NEURAL FUZZY MODELS BASED ON REINFORCEMENT LEARNING OF INTELLIGENT AGENTS
Tese