André Carlos Ponce de Leon Ferreira de Carvalho

Artificial Intelligence · 2009–2020

A researcher in the Science corpus: 7 papers; trusts 22 researchers and is trusted by 16 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 114 citations into it; #9,299 of 35,345 by trust here, #10,942 by citations
• Computer Vision and Pattern Recognition — 43 citations into it
• Signal Processing — 20 citations into it
• Information Systems — 19 citations into it
• Statistical Learning Theory — 17 citations into it
• Computational Theory and Mathematics — 11 citations into it; #4,465 of 12,182 by trust here, #5,465 by citations
• Computer Networks and Communications — 11 citations into it
• Algorithms & Complexity — 7 citations into it

Whom André Carlos Ponce de Leon Ferreira de Carvalho trusts overall

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

1. J. Ross Quinlan
2. Sanghamitra Bandyopadhyay
3. S. Sathiya Keerthi
4. David E. Goldberg
5. Ujjwal Maulik
6. Shawkat Ali
7. John R. Koza
8. Niko Speybroeck
9. Sreerama K. Murthy
10. Vladimir Naumovich Vapnik

Who trusts André Carlos Ponce de Leon Ferreira de Carvalho overall

1. Marc-André Zöller
2. Marco F. Huber
3. Emilio Carrizosa
4. Matthias Feurer
5. Gilles Vandewiele
6. Martin Wistuba
7. Agoston E. Eiben

Papers from André Carlos Ponce de Leon Ferreira de Carvalho's perspective

Ordered by how strongly the researchers André Carlos Ponce de Leon Ferreira de Carvalho trusts endorse each paper. Same corpus, a different order for every researcher.

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

Their papers

• Combining meta-learning and search techniques to select parameters for support vector machines (2012) — 167 citations
• MeLIME: Meaningful Local Explanation for Machine Learning Models (2020) — 21 citations
• Endowing a Content-Based Medical Image Retrieval System with Perceptual Similarity Using Ensemble Strategy (2016) — 24 citations
• Data stream clustering: A survey (2013) — 571 citations
• A Survey of Evolutionary Algorithms for Decision-Tree Induction (2012) — 354 citations
• An Experimental Study of the Combination of Meta-Learning with Particle Swarm Algorithms for SVM Parameter Selection (2012) — 14 citations
• A Survey of Evolutionary Algorithms for Clustering (2009) — 755 citations