Sebastián Maldonado

Artificial Intelligence · 2009–2019

A researcher in the Science corpus: 4 papers; trusts 25 researchers and is trusted by 19 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 20 citations into it; #9,795 of 35,345 by trust here, #17,412 by citations
• Optimization & Training — 7 citations into it
• Statistical Learning Theory — 6 citations into it
• Molecular Biology — 5 citations into it; #2,787 of 17,773 by trust here, #10,695 by citations

Whom Sebastián Maldonado trusts overall

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

1. Yuhai Wu
2. Alain Rakotomamonjy
3. Isabelle M Guyon
4. Jason Aaron Edward Weston
5. Paul S. Bradley
6. John Shawe-Taylor
7. Andre´ Elisseeff
8. Gunnar Rätsch
9. David Martinus Johannes Tax
10. Bernhard Schölkopf

Who trusts Sebastián Maldonado overall

1. Jessie Y.C. Chen
2. Haoyue Liu
3. Min-Ling Zhang
4. Verónica Bolón-Canedo
5. Harsurinder Kaur
6. Alan Jović
7. Wing W. Y. Ng
8. Michael J. Barnes
9. Richard Weber
10. José María Peña Sánchez

Papers from Sebastián Maldonado's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. ImageNet: A large-scale hierarchical image database
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• A wrapper method for feature selection using Support Vector Machines (2009) — 465 citations
• Feature selection for high-dimensional class-imbalanced data sets using Support Vector Machines (2014) — 303 citations
• Hierarchical time series forecasting via Support Vector Regression in the European Travel Retail Industry (2019) — 73 citations
• Advanced conjoint analysis using feature selection via support vector machines (2015) — 40 citations