Bekir Sait Ciftler

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 12 citations into it
• Optimization & Training — 8 citations into it
• Federated & Distributed Learning — 5 citations into it

Whom Bekir Sait Ciftler trusts overall

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

1. Virginia Smith
2. Pierre Sermanet
3. Yann LeCun
4. Tao Lin
5. H. Brendan McMahan
6. Ofer Dekel

Papers from Bekir Sait Ciftler's perspective

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

1. Gradient-based learning applied to document recognition
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. ImageNet classification with deep convolutional neural networks
4. Long Short-Term Memory
5. Learning Multiple Layers of Features from Tiny Images
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
8. ImageNet: A large-scale hierarchical image database
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. TensorFlow: A system for large-scale machine learning

Their papers

• Exploiting Unlabeled Data in Smart Cities using Federated Learning (2020) — 20 citations