Tibério S. Caetano
Artificial Intelligence · 2007–2016
A researcher in the Science corpus: 7 papers; trusts 30 researchers and is trusted by 38 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 46 citations into it; #4,804 of 35,345 by trust here, #9,092 by citations
- Computer Vision and Pattern Recognition — 19 citations into it; #4,556 of 21,575 by trust here, #8,021 by citations
- Statistical Learning Theory — 19 citations into it
- Management Science and Operations Research — 14 citations into it
- Optimization & Training — 13 citations into it; #568 of 2,601 by trust here, #1,385 by citations
- Statistics and Probability — 13 citations into it
- Computational Mechanics — 12 citations into it; #1,009 of 10,001 by trust here, #3,190 by citations
- Control and Systems Engineering — 8 citations into it
Whom Tibério S. Caetano trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- David G. Lowe
- Alex Smola
- Bernhard Schölkopf
- Serge J. Belongie
- Yasemin Altun
- Jitendra Malik
- Geoffrey E. Hinton
- Thorsten Joachims
- Shai Shalev-Shwartz
- Dimitri P. Bertsekas
Who trusts Tibério S. Caetano overall
- Quanshi Zhang
- Giorgio Patrini
- Aaron Defazio
- Zeyuan Allen-Zhu
- Simon Lacoste-Julien
- Lorenzo Torresani
- Julian McAuley
- Deepti Pachauri
- Jiayi Ma
- Richard Nock
Papers from Tibério S. Caetano's perspective
Ordered by how strongly the researchers Tibério S. Caetano 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)
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- 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
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Learning Graph Matching (2007) — 465 citations
- Finito: A faster, permutable incremental gradient method for big data problems (2014) — 172 citations
- Estimating labels from label proportions (2008) — 276 citations
- Fast Learning from Distributed Datasets without Entity Matching (2016) — 12 citations
- A Hybrid Loss for Multiclass and Structured Prediction (2014) — 7 citations
- (Almost) No Label No Cry (2014) — 122 citations
- Multitask Learning without Label Correspondences (2010) — 44 citations