Carlos Soares

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Universidade do Porto

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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...
10/22/2020 ∙ by Vítor Cerqueira, et al. ∙ 0 ∙ share

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VEST: Automatic Feature Engineering for Forecasting

Time series forecasting is a challenging task with applications in a wid...
10/14/2020 ∙ by Vítor Cerqueira, et al. ∙ 66 ∙ share

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A Bandit-Based Algorithm for Fairness-Aware Hyperparameter Optimization

Considerable research effort has been guided towards algorithmic fairnes...
10/07/2020 ∙ by André F. Cruz, et al. ∙ 0 ∙ share

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Machine Learning vs Statistical Methods for Time Series Forecasting: Size Matters

Time series forecasting is one of the most active research topics. Machi...
09/29/2019 ∙ by Vítor Cerqueira, et al. ∙ 0 ∙ share

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Preference rules for label ranking: Mining patterns in multi-target relations

In this paper we investigate two variants of association rules for prefe...
03/20/2019 ∙ by Cláudio Rebelo de Sá, et al. ∙ 0 ∙ share

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Entity-Relationship Search over the Web

Entity-Relationship (E-R) Search is a complex case of Entity Search wher...
10/08/2018 ∙ by Pedro Saleiro, et al. ∙ 0 ∙ share

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cf2vec: Collaborative Filtering algorithm selection using graph distributed representations

Algorithm selection using Metalearning aims to find mappings between pro...
09/17/2018 ∙ by Tiago Cunha, et al. ∙ 0 ∙ share

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Towards Reproducible Empirical Research in Meta-Learning

Meta-learning is increasingly used to support the recommendation of mach...
08/30/2018 ∙ by Adriano Rivolli, et al. ∙ 0 ∙ share

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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...
07/23/2018 ∙ by Tiago Cunha, et al. ∙ 0 ∙ share

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Building robust prediction models for defective sensor data using Artificial Neural Networks

Predicting the health of components in complex dynamic systems such as a...
04/16/2018 ∙ by Arvind Kumar Shekar, et al. ∙ 0 ∙ share

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CF4CF: Recommending Collaborative Filtering algorithms using Collaborative Filtering

Automatic solutions which enable the selection of the best algorithms fo...
03/06/2018 ∙ by Tiago Cunha, et al. ∙ 0 ∙ share

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Smart energy management as a means towards improved energy efficiency

The costs associated with refrigerator equipment often represent more th...
02/08/2018 ∙ by Dylan te Lindert, et al. ∙ 0 ∙ share

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Learning Word Embeddings from the Portuguese Twitter Stream: A Study of some Practical Aspects

This paper describes a preliminary study for producing and distributing ...
09/04/2017 ∙ by Pedro Saleiro, et al. ∙ 0 ∙ share

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autoBagging: Learning to Rank Bagging Workflows with Metalearning

Machine Learning (ML) has been successfully applied to a wide range of d...
06/28/2017 ∙ by Fábio Pinto, et al. ∙ 0 ∙ share

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FEUP at SemEval-2017 Task 5: Predicting Sentiment Polarity and Intensity with Financial Word Embeddings

This paper presents the approach developed at the Faculty of Engineering...
04/17/2017 ∙ by Pedro Saleiro, et al. ∙ 0 ∙ share

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