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07/10/2021
Meta-aprendizado para otimizacao de parametros de redes neurais
The optimization of Artificial Neural Networks (ANNs) is an important ta...
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06/25/2021
Pastprop-RNN: improved predictions of the future by correcting the past
Forecasting accuracy is reliant on the quality of available past data. D...
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04/05/2021
Model Compression for Dynamic Forecast Combination
The predictive advantage of combining several different predictive model...
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04/01/2021
Model Selection for Time Series Forecasting: Empirical Analysis of Different Estimators
Evaluating predictive models is a crucial task in predictive analytics. ...
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03/23/2021
Promoting Fairness through Hyperparameter Optimization
Considerable research effort has been guided towards algorithmic fairnes...
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03/09/2021
u-cf2vec: Representation Learning for Personalized Algorithm Selection in Recommender Systems
Collaborative Filtering (CF) has become the standard approach to solve r...
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10/22/2020
Early Anomaly Detection in Time Series: A Hierarchical Approach for Predicting Critical Health Episodes
The early detection of anomalous events in time series data is essential...
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10/14/2020
VEST: Automatic Feature Engineering for Forecasting
Time series forecasting is a challenging task with applications in a wid...
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10/07/2020
A Bandit-Based Algorithm for Fairness-Aware Hyperparameter Optimization
Considerable research effort has been guided towards algorithmic fairnes...
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09/29/2019
Machine Learning vs Statistical Methods for Time Series Forecasting: Size Matters
Time series forecasting is one of the most active research topics. Machi...
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03/20/2019
Preference rules for label ranking: Mining patterns in multi-target relations
In this paper we investigate two variants of association rules for prefe...
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10/08/2018
Entity-Relationship Search over the Web
Entity-Relationship (E-R) Search is a complex case of Entity Search wher...
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09/17/2018
cf2vec: Collaborative Filtering algorithm selection using graph distributed representations
Algorithm selection using Metalearning aims to find mappings between pro...
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08/30/2018
Towards Reproducible Empirical Research in Meta-Learning
Meta-learning is increasingly used to support the recommendation of mach...
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07/23/2018
Algorithm Selection for Collaborative Filtering: the influence of graph metafeatures and multicriteria metatargets
To select the best algorithm for a new problem is an expensive and diffi...
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04/16/2018
Building robust prediction models for defective sensor data using Artificial Neural Networks
Predicting the health of components in complex dynamic systems such as a...
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03/06/2018
CF4CF: Recommending Collaborative Filtering algorithms using Collaborative Filtering
Automatic solutions which enable the selection of the best algorithms fo...
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02/08/2018
Smart energy management as a means towards improved energy efficiency
The costs associated with refrigerator equipment often represent more th...
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09/04/2017
Learning Word Embeddings from the Portuguese Twitter Stream: A Study of some Practical Aspects
This paper describes a preliminary study for producing and distributing ...
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06/28/2017
autoBagging: Learning to Rank Bagging Workflows with Metalearning
Machine Learning (ML) has been successfully applied to a wide range of d...
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04/17/2017