Giorgio Valentini
Artificial Intelligence · with Zhang · 2002–2019
A researcher in the Science corpus: 3 papers; trusts 19 researchers and is trusted by 8 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 12 citations into it; #17,006 of 35,345 by trust here, #29,412 by citations
- Statistical Learning Theory — 9 citations into it
- Evaluation & Benchmarks — 6 citations into it
- Optimization & Training — 6 citations into it
- Statistics and Probability — 6 citations into it
Whom Giorgio Valentini trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Robert E. Schapire
- Jerome H. Friedman
- Thomas G. Dietterich
- Yoav Freund
- Leo Breiman
- J. Ross Quinlan
- Tin Kam Ho
- Trevor J. Hastie
- Yoram Singer
- Holger Schwenk
Who trusts Giorgio Valentini overall
- Arthur Zimek
- Eugene Tuv
- Ricardo José Gabrielli Barreto Campello
- Alexander Borisov
- William J. Tastle
- Jörg Sander
- Massimo Buscema
- Petr Kadlec
- George C. Runger
Papers from Giorgio Valentini's perspective
Ordered by how strongly the researchers Giorgio Valentini 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
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
Their papers
- The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens (2019) — 434 citations
- A Whole-Genome Analysis Framework for Effective Identification of Pathogenic Regulatory Variants in Mendelian Disease. (2016) — 252 citations
- Ensembles of Learning Machines (2002) — 330 citations