Ali Rahimi
Artificial Intelligence · 2007–2017
A researcher in the Science corpus: 5 papers; trusts 29 researchers and is trusted by 392 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 45 citations into it; #15,970 of 35,345 by trust here, #15,236 by citations
- Computer Vision and Pattern Recognition — 30 citations into it
- Statistical Learning Theory — 25 citations into it; #145 of 1,038 by trust here, #279 by citations
- Optimization & Training — 22 citations into it
- Computational Mechanics — 10 citations into it; #4,491 of 10,001 by trust here, #4,937 by citations
- Scaling & Learning Theory — 8 citations into it
- Statistics and Probability — 8 citations into it
- Algorithms & Complexity — 5 citations into it
Whom Ali Rahimi trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Robert E. Schapire
- Andrew R. Barron
- Eric R. Ziegel
- Jerome H. Friedman
- Peter L. Bartlett
- Yuhai Wu
- B. Recht
- Ivor Wai-Hung Tsang
- Shahar Mendelson
- Shai Shalev-Shwartz
Who trusts Ali Rahimi overall
- Francis R. Bach
- David Lopez-Paz
- Bo Dai
- João Carreira
- Krzysztof Marcin Choromanski
- Quoc V. Le
- Andrew Gordon Wilson
- Yunchao Gong
- Qiang Liu
- Bernhard Schölkopf
Papers from Ali Rahimi's perspective
Ordered by how strongly the researchers Ali Rahimi 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)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- 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)
Their papers
- Similarity-based Classification: Concepts and Algorithms (2009) — 404 citations
- Uniform approximation of functions with random bases (2008) — 305 citations
- Convergence Results for Neural Networks via Electrodynamics (2017) — 22 citations
- Weighted Sums of Random Kitchen Sinks: Replacing minimization with randomization in learning (2008) — 866 citations
- Random Features for Large-Scale Kernel Machines (2007) — 5,023 citations