Alberto Fernández

Artificial Intelligence · Pattern Recognition · 2008–2019

A researcher in the Science corpus: 15 papers; trusts 112 researchers and is trusted by 50 researchers here, as inferred from the citation graph.

Subfields

Artificial Intelligence — 300 citations into it; #4,122 of 35,345 by trust here, #2,953 by citations
Information Systems — 83 citations into it; #6,000 of 8,771 by trust here, #4,885 by citations
Electrical and Electronic Engineering — 56 citations into it; #2,576 of 16,539 by trust here, #3,169 by citations
Statistics and Probability — 49 citations into it; #3,724 of 12,932 by trust here, #2,579 by citations
Computer Vision and Pattern Recognition — 33 citations into it
Computational Theory and Mathematics — 32 citations into it
Evaluation & Benchmarks — 31 citations into it; #2,860 of 3,147 by trust here, #1,542 by citations
Accounting — 28 citations into it; #8,038 of 8,970 by trust here, #5,847 by citations

Whom Alberto Fernández trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

Who trusts Alberto Fernández overall

Papers from Alberto Fernández's perspective

Ordered by how strongly the researchers Alberto Fernández trusts endorse each paper. Same corpus, a different order for every researcher.

ImageNet classification with deep convolutional neural networks
Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
Gradient-based learning applied to document recognition
Long Short-Term Memory
ImageNet: A large-scale hierarchical image database
Attention is All you Need (Neural Information Processing Systems)
Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Learning Multiple Layers of Features from Tiny Images
Going deeper with convolutions

Their papers

A Review on Ensembles for the Class Imbalance Problem: Bagging-, Boosting-, and Hybrid-Based Approaches (2012) — 1,775 citations
Evolutionary Fuzzy Systems for Explainable Artificial Intelligence: Why, When, What for, and Where to? (2019) — 189 citations
Big Data: Tutorial and guidelines on information and process fusion for analytics algorithms with MapReduce (2018) — 132 citations
An insight into classification with imbalanced data: Empirical results and current trends on using data intrinsic characteristics (2013) — 1,580 citations
Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power (2010) — 2,151 citations
Analysing the classification of imbalanced data-sets with multiple classes: Binarization techniques and ad-hoc approaches (2013) — 390 citations
Analysis of preprocessing vs. cost-sensitive learning for imbalanced classification. Open problems on intrinsic data characteristics (2012) — 312 citations
SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year Anniversary (2018) — 2,068 citations
Learning from Imbalanced Data Sets (2018) — 1,073 citations
EUSBoost: Enhancing ensembles for highly imbalanced data-sets by evolutionary undersampling (2013) — 399 citations
An overview of ensemble methods for binary classifiers in multi-class problems: Experimental study on one-vs-one and one-vs-all schemes (2011) — 779 citations
KEEL Data-Mining Software Tool: Data Set Repository, Integration of Algorithms and Experimental Analysis Framework (2011) — 2,449 citations
Enhancing the effectiveness and interpretability of decision tree and rule induction classifiers with evolutionary training set selection over imbalanced problems (2009) — 109 citations
A study of statistical techniques and performance measures for genetics-based machine learning: accuracy and interpretability (2009) — 697 citations
A study of the behaviour of linguistic fuzzy rule based classification systems in the framework of imbalanced data-sets (2008) — 323 citations