Itamar Arel

Computer Vision and Pattern Recognition · 2009–2015

A researcher in the Science corpus: 9 papers; trusts 109 researchers and is trusted by 48 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 33 citations into it; #5,355 of 21,575 by trust here, #5,507 by citations
• Artificial Intelligence — 30 citations into it; #4,986 of 35,345 by trust here, #6,911 by citations
• Model Architectures — 21 citations into it
• Optimization & Training — 15 citations into it
• Representation & Self-Supervised Learning — 15 citations into it
• Reinforcement Learning — 11 citations into it
• Cognitive Neuroscience — 6 citations into it
• Evaluation & Benchmarks — 6 citations into it

Whom Itamar Arel trusts overall

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

1. Geoffrey E. Hinton
2. Kunihiko Fukushima
3. Yoshua Bengio
4. Yann LeCun
5. R. M. French
6. Alex Krizhevsky
7. Ian J. Goodfellow
8. Ilya Sutskever
9. Jimmy Ba
10. Diederik P. Kingma

Who trusts Itamar Arel overall

1. Benjamin Goodrich
2. Yanming Guo
3. Heechul Jung
4. Xueni Pan
5. Hua Wei
6. Stefan Feuerriegel
7. Yuhao Wang
8. Roberto Minerva
9. José Hernandez-Orallo
10. Jeongwoo Ju

Papers from Itamar Arel's perspective

Ordered by how strongly the researchers Itamar Arel 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Going deeper with convolutions

Their papers

• Low-Rank Approximations for Conditional Feedforward Computation in Deep Neural Networks (2013) — 88 citations
• Deep Machine Learning - A New Frontier in Artificial Intelligence Research [Research Frontier] (2010) — 1,183 citations
• Mitigating Catastrophic Forgetting in Temporal Difference Learning with Function Approximation (2015)
• Sequential Covariance-Matrix Estimation with Application to Mitigating Catastrophic Forgetting (2015) — 7 citations
• Neuron clustering for mitigating catastrophic forgetting in feedforward neural networks (2014) — 8 citations
• Unsupervised neuron selection for mitigating catastrophic forgetting in neural networks (2014) — 20 citations
• Mitigation of catastrophic forgetting in recurrent neural networks using a Fixed Expansion Layer (2013) — 20 citations
• Reinforcement learning-based multi-agent system for network traffic signal control (2010) — 520 citations
• Beyond the Turing Test (2009) — 144 citations