Noelia Sánchez-Maroño

Artificial Intelligence · 2007–2016

A researcher in the Science corpus: 5 papers; trusts 36 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 67 citations into it; #15,387 of 35,345 by trust here, #13,962 by citations
• Molecular Biology — 52 citations into it; #6,073 of 17,773 by trust here, #8,182 by citations
• Computer Vision and Pattern Recognition — 29 citations into it; #9,849 of 21,575 by trust here, #9,563 by citations
• Information Systems — 17 citations into it; #6,535 of 8,771 by trust here, #7,386 by citations
• Evaluation & Benchmarks — 13 citations into it
• Computational Theory and Mathematics — 7 citations into it
• Statistics and Probability — 6 citations into it
• Computational Biology & Bioinformatics — 5 citations into it

Whom Noelia Sánchez-Maroño trusts overall

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

1. Huan Liu
2. Lei Yu
3. Mark A. Hall
4. Igor Kononenko
5. Zheng Zhao
6. George Forman
7. Verónica Bolón-Canedo
8. Manoranjan Dash
9. Aixia Guo
10. Salvador Garcia

Who trusts Noelia Sánchez-Maroño overall

1. Verónica Bolón-Canedo
2. Aisha Abdallah
3. Amparo Alonso-Betanzos
4. Bilal Mirza
5. Vipin Kumar
6. Mohd Aizaini Maarof
7. Haoyue Liu
8. Ryan J. Urbanowicz
9. Wei Wang

Papers from Noelia Sánchez-Maroño's perspective

Ordered by how strongly the researchers Noelia Sánchez-Maroño trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Gradient-based learning applied to document recognition
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. An Introduction to Variable and Feature Selection
6. Wrappers for Feature Subset Selection
7. Attention is All you Need (Neural Information Processing Systems)
8. Estimating Attributes: Analysis and Extensions of RELIEF
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet: A large-scale hierarchical image database

Their papers

• A review of feature selection methods on synthetic data (2013) — 836 citations
• A review of microarray datasets and applied feature selection methods (2014) — 638 citations
• Recent advances and emerging challenges of feature selection in the context of big data (2015) — 328 citations
• Feature selection for high-dimensional data (2016) — 388 citations
• Filter Methods for Feature Selection - A Comparative Study (2007) — 427 citations