Raffaello Camoriano
Artificial Intelligence · 2015–2016
A researcher in the Science corpus: 4 papers; trusts 15 researchers and is trusted by 5 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 34 citations into it
- Computational Mechanics — 21 citations into it; #4,973 of 10,001 by trust here, #6,582 by citations
- Computer Vision and Pattern Recognition — 21 citations into it
- Statistical Learning Theory — 19 citations into it
- Optimization & Training — 13 citations into it
- Mathematical Physics — 10 citations into it; #4,620 of 8,562 by trust here, #4,500 by citations
- Applied Mathematics — 5 citations into it
- Control and Systems Engineering — 5 citations into it
Whom Raffaello Camoriano trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Christopher K. I. Williams
- Alex Krizhevsky
- Geoffrey E. Hinton
- Charles Peter Elkan
- Yangqing Jia
- Alex Smola
- Alex Gittens
- Yann LeCun
- Yoshua Bengio
- Michael W. Mahoney
Who trusts Raffaello Camoriano overall
- Alessandro Rudi
- Carlo Ciliberto
- Gyuhak Kim
- Masood Dehghan
- Krzysztof Marcin Choromanski
- Luigi Carratino
- Zoltán Szabó
- Ulysse Marteau-Ferey
- Vincenzo Lomonaco
- Lorenzo Rosasco
Papers from Raffaello Camoriano's perspective
Ordered by how strongly the researchers Raffaello Camoriano 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)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet Large Scale Visual Recognition Challenge
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Incremental Object Recognition in Robotics with Extension to New Classes in Constant Time (2016) — 5 citations
- Incremental robot learning of new objects with fixed update time (2016) — 44 citations
- Less is More: Nystr\"om Computational Regularization (2015) — 128 citations
- Less is More: Nyström Computational Regularization (2015) — 299 citations