Luca Saglietti

Computer Vision and Pattern Recognition · 2015–2016

A researcher in the Science corpus: 4 papers; trusts 4 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 8 citations into it

Whom Luca Saglietti trusts overall

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

1. Yoshua Bengio
2. Yann LeCun
3. Simon S. Haykin
4. Bart Kosko

Who trusts Luca Saglietti overall

1. Carlo Baldassi
2. Pratik Chaudhari
3. Fabrizio Pittorino

Papers from Luca Saglietti's perspective

Ordered by how strongly the researchers Luca Saglietti 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. GradientBased Learning Applied to Document Recognition
4. Learning representations by back-propagating errors
5. Representation Learning: A Review and New Perspectives
6. Untersuchungen zu dynamischen neuronalen Netzen
7. Information Theory, Inference, and Learning Algorithms
8. BinaryConnect: Training Deep Neural Networks with binary weights during propagations
9. Deep learning with Elastic Averaging SGD
10. ImageNet classification with deep convolutional neural networks

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
• Learning may need only a few bits of synaptic precision. (2016) — 29 citations
• Local entropy as a measure for sampling solutions in constraint satisfaction problems (2015) — 71 citations