Anupam Datta

Artificial Intelligence · 2006–2020

A researcher in the Science corpus: 17 papers; trusts 170 researchers and is trusted by 63 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 208 citations into it; #4,235 of 35,345 by trust here, #3,183 by citations
• Safety, Robustness & Interpretability — 57 citations into it; #419 of 2,251 by trust here, #427 by citations
• Privacy & Security — 46 citations into it; #243 of 709 by trust here, #131 by citations
• Computational Theory and Mathematics — 39 citations into it; #8,423 of 12,182 by trust here, #7,851 by citations
• Computer Vision and Pattern Recognition — 38 citations into it
• Natural Language Processing — 35 citations into it; #2,980 of 5,688 by trust here, #2,307 by citations
• Signal Processing — 34 citations into it
• Sociology and Political Science — 30 citations into it; #3,179 of 22,756 by trust here, #2,135 by citations

Whom Anupam Datta trusts overall

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

1. Cynthia Dwork
2. Frank McSherry
3. Robert Tibshirani
4. Lloyd S. Shapley
5. Moritz Hardt
6. Stefan Rüping
7. Latanya Sweeney
8. Kobbi Nissim
9. Alex Krizhevsky
10. Avrim Blum

Who trusts Anupam Datta overall

1. Scott M. Lundberg
2. Mukund Sundararajan
3. Ian Covert
4. Su-In Lee
5. Giulia Vilone
6. Luke Merrick
7. Nadia Burkart
8. Gabriel Erion-Barner
9. Simon Caton
10. Ankur Taly

Papers from Anupam Datta's perspective

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

Their papers

• Gender Bias in Neural Natural Language Processing (2018) — 408 citations
• Feature-Wise Bias Amplification (2018) — 52 citations
• Algorithmic Transparency via Quantitative Input Influence: Theory and Experiments with Learning Systems (2016) — 783 citations
• Influence Paths for Characterizing Subject-Verb Number Agreement in LSTM Language Models (2020) — 10 citations
• Differentially private data analysis of social networks via restricted sensitivity (2012) — 245 citations
• Automated Experiments on Ad Privacy Settings (2014) — 784 citations
• Differentially Private Password Frequency Lists (2016) — 62 citations
• Formal Verification of Differential Privacy for Interactive Systems (2011) — 46 citations
• Privacy and contextual integrity: framework and applications (2006) — 525 citations
• Formal Verification of Differential Privacy for Interactive Systems (Extended Abstract) (2011) — 24 citations
• Discrimination in Online Advertising: A Multidisciplinary Inquiry (2018) — 58 citations
• Influence-Directed Explanations for Deep Convolutional Networks (2018) — 80 citations
• Proxy Non-Discrimination in Data-Driven Systems (2017) — 59 citations
• überSpark: Enforcing Verifiable Object Abstractions for Automated Compositional Security Analysis of a Hypervisor (2016) — 40 citations
• The Johnson-Lindenstrauss Transform Itself Preserves Differential Privacy (2012) — 262 citations
• TrustVisor: Efficient TCB Reduction and Attestation (2010) — 649 citations
• Efficient TCB Reduction and Attestation (2009)