Alessandro Ingrosso

Computer Vision and Pattern Recognition · 2015–2016

A researcher in the Science corpus: 3 papers; trusts 4 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 7 citations into it

Whom Alessandro Ingrosso trusts overall

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

1. Yann LeCun
2. Simon S. Haykin
3. E. Gardner
4. Carlo Baldassi
5. Yoshua Bengio
6. Geoffrey E. Hinton

Who trusts Alessandro Ingrosso overall

1. Carlo Baldassi
2. Pratik Chaudhari
3. Riccardo Zecchina
4. Gintare Karolina Dziugaite
5. Fabrizio Pittorino
6. Stefano Soatto
7. Matthieu Courbariaux

Papers from Alessandro Ingrosso's perspective

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

1. Gradient-based learning applied to document recognition
2. A Fast Learning Algorithm for Deep Belief Nets
3. ImageNet classification with deep convolutional neural networks
4. GradientBased Learning Applied to Document Recognition
5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
6. Long Short-Term Memory
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Learning Multiple Layers of Features from Tiny Images
9. Learning representations by back-propagating errors
10. Representation Learning: A Review and New Perspectives

Their papers

• Subdominant Dense Clusters Allow for Simple Learning and High Computational Performance in Neural Networks with Discrete Synapses. (2015) — 152 citations
• Unreasonable effectiveness of learning neural networks: From accessible states and robust ensembles to basic algorithmic schemes (2016) — 183 citations
• Local entropy as a measure for sampling solutions in constraint satisfaction problems (2015) — 71 citations