Hussain Alibrahim

IEEE Congress on Evolutionary Computation · 2021

A researcher in the Science corpus: 1 paper; trusts 13 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Whom Hussain Alibrahim trusts overall

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

1. Thorsten Joachims
2. Gang Luo
3. James Bergstra
4. Roweida Mohammed
5. Bernd Bischl
6. Yoshua Bengio
7. Sebastian Ruder
8. Mohammed J. Zaki
9. Jumanah Rawashdeh
10. Olaf Mersmann

Papers from Hussain Alibrahim's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. Learning Multiple Layers of Features from Tiny Images
8. ImageNet: A large-scale hierarchical image database
9. Going deeper with convolutions
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Hyperparameter Optimization: Comparing Genetic Algorithm against Grid Search and Bayesian Optimization (2021) — 359 citations