Matilde Gargiani
Artificial Intelligence · 2017–2018
A researcher in the Science corpus: 2 papers; trusts 36 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 23 citations into it
- Computational Mechanics — 22 citations into it
- Optimization & Training — 19 citations into it
- Numerical Analysis — 9 citations into it
- Computational Theory and Mathematics — 5 citations into it
- Federated & Distributed Learning — 5 citations into it
Whom Matilde Gargiani trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Francis R. Bach
- Shai Shalev-Shwartz
- Yurii E. Nesterov
- Paul Tseng
- Jorge Nocedal
- Stephen J. Wright
- Martin Jaggi
- Virginia Smith
- Tong Zhang
- Martin Takác
Who trusts Matilde Gargiani overall
- Lie He
- Virginia Smith
- An Bian
- Celestine Mendler-Dünner
- Martin Jaggi
- Simone Forte
- Aurélien Lucchi
- Chenxin Ma
- Martin Takác
Papers from Matilde Gargiani's perspective
Ordered by how strongly the researchers Matilde Gargiani trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Long Short-Term Memory
- Learning Multiple Layers of Features from Tiny Images
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)