Ali Anwar

Artificial Intelligence · 2018–2020

A researcher in the Science corpus: 6 papers; trusts 24 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 116 citations into it; #16,667 of 35,345 by trust here, #10,430 by citations
• Privacy & Security — 49 citations into it
• Federated & Distributed Learning — 36 citations into it
• Computational Theory and Mathematics — 14 citations into it
• Safety, Robustness & Interpretability — 13 citations into it
• Sociology and Political Science — 12 citations into it

Whom Ali Anwar trusts overall

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

1. Cynthia Dwork
2. Reza Shokri
3. Ivan Bjerre Damgård
4. J. Ross Quinlan
5. Oded Goldreich
6. H. Brendan McMahan
7. Milad Nasr
8. Peter Kairouz
9. Martín Abadi
10. Ilya Mironov

Who trusts Ali Anwar overall

1. Li Li
2. Haokun Fang
3. Xuefei Yin
4. Latif Ullah Khan

Papers from Ali Anwar's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Gradient-based learning applied to document recognition
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Learning Multiple Layers of Features from Tiny Images
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. ImageNet: A large-scale hierarchical image database
7. Deep Learning with Differential Privacy
8. Deep Learning
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Membership Inference Attacks Against Machine Learning Models

Their papers

• A Hybrid Approach to Privacy-Preserving Federated Learning (2018) — 1,112 citations
• IBM Federated Learning: an Enterprise Framework White Paper V0.1 (2020) — 198 citations
• TiFL: A Tier-based Federated Learning System (2020) — 370 citations
• HybridAlpha: An Efficient Approach for Privacy-Preserving Federated Learning (2019) — 321 citations
• Towards Federated Graph Learning for Collaborative Financial Crimes Detection (2019) — 82 citations
• Towards Taming the Resource and Data Heterogeneity in Federated Learning (2019) — 94 citations