Ayfer Özgür
Artificial Intelligence · 2006–2021
A researcher in the Science corpus: 13 papers; trusts 109 researchers and is trusted by 12 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 201 citations into it; #18,748 of 35,345 by trust here, #19,018 by citations
- Statistics and Probability — 87 citations into it; #2,372 of 12,932 by trust here, #2,309 by citations
- Computer Networks and Communications — 65 citations into it; #1,542 of 9,886 by trust here, #1,912 by citations
- Privacy & Security — 63 citations into it; #497 of 709 by trust here, #642 by citations
- Electrical and Electronic Engineering — 46 citations into it; #8,554 of 16,539 by trust here, #9,210 by citations
- Computational Mechanics — 42 citations into it
- Statistical Learning Theory — 42 citations into it; #428 of 1,038 by trust here, #577 by citations
- Optimization & Training — 42 citations into it
Whom Ayfer Özgür trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yanjun Han
- John C. Duchi
- Jayadev Acharya
- Leighton Pate Barnes
- Roman Vershynin
- A. Garg
- Cynthia Dwork
- Yuchen Zhang
- Alexandre B. Tsybakov
- Peter Kairouz
Who trusts Ayfer Özgür overall
- Leighton Pate Barnes
- Jayadev Acharya
- Wei-Ning Chen
- Yanjun Han
- Clément Louis Canonne
- Peter Kairouz
- Himanshu Tyagi
- Ziteng Sun
- Yuan Shen
- Hariharan Rahul
Papers from Ayfer Özgür's perspective
Ordered by how strongly the researchers Ayfer Özgür trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Long Short-Term Memory
- 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)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Hierarchical Cooperation Achieves Optimal Capacity Scaling in Ad Hoc Networks (2006) — 695 citations
- Geometric Lower Bounds for Distributed Parameter Estimation Under Communication Constraints (2018) — 101 citations
- Distributed Statistical Estimation of High-Dimensional and Nonparametric Distributions (2018) — 54 citations
- Fisher Information for Distributed Estimation under a Blackboard Communication Protocol (2019) — 29 citations
- Learning Distributions from their Samples under Communication Constraints (2019) — 18 citations
- A Geometric Characterization of Fisher Information from Quantized Samples with Applications to Distributed Statistical Estimation (2018) — 12 citations
- Breaking the Communication-Privacy-Accuracy Trilemma (2020) — 139 citations
- Breaking The Dimension Dependence in Sparse Distribution Estimation under Communication Constraints (2021) — 11 citations
- Differentially Private Federated Learning: An Information-Theoretic Perspective (2021) — 31 citations
- Fisher Information Under Local Differential Privacy (2020) — 60 citations
- rTop-k: A Statistical Estimation Approach to Distributed SGD (2020) — 71 citations
- Lower Bounds for Learning Distributions under Communication Constraints via Fisher Information (2019) — 82 citations
- Minimax Bounds for Distributed Logistic Regression (2019) — 5 citations