Claire Monteleoni

Artificial Intelligence · 2003–2013

A researcher in the Science corpus: 6 papers; trusts 38 researchers and is trusted by 267 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 64 citations into it; #12,676 of 35,345 by trust here, #19,018 by citations
• Privacy & Security — 34 citations into it; #560 of 709 by trust here, #708 by citations
• Sociology and Political Science — 16 citations into it
• Computational Theory and Mathematics — 15 citations into it; #4,362 of 12,182 by trust here, #4,696 by citations
• Statistics and Probability — 14 citations into it
• Statistical Learning Theory — 12 citations into it
• Safety, Robustness & Interpretability — 7 citations into it; #44 of 2,251 by trust here, #149 by citations
• Computer Science Applications — 6 citations into it; #1,240 of 1,855 by trust here, #1,797 by citations

Whom Claire Monteleoni trusts overall

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

1. Cynthia Dwork
2. Frank McSherry
3. Per Austrin
4. Avrim Blum
5. Mark Herbster
6. Kamalika Chaudhuri
7. Kobbi Nissim
8. Yoav Freund
9. Manfred K. Warmuth
10. Shai Shalev-Shwartz

Who trusts Claire Monteleoni overall

1. Abhradeep Thakurta
2. Reza Shokri
3. Prateek Jain
4. Kamalika Chaudhuri
5. Yu-Xiang Wang
6. Vitaly Feldman
7. Nicholas Carlini
8. Nicolas Papernot
9. Peter Kairouz
10. Raef Bassily

Papers from Claire Monteleoni's perspective

Ordered by how strongly the researchers Claire Monteleoni 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. Calibrating Noise to Sensitivity in Private Data Analysis
5. Learning Multiple Layers of Features from Tiny Images
6. Differential Privacy
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. ImageNet: A large-scale hierarchical image database
9. Practical privacy: the SuLQ framework
10. Towards Sharp Inapproximability For Any 2-CSP

Their papers

• Analysis of Perceptron-Based Active Learning (2009) — 300 citations
• A Semi-Supervised Learning Approach to Differential Privacy (2013) — 24 citations
• Differentially Private Empirical Risk Minimization (2009) — 1,610 citations
• Privacy-preserving logistic regression (2008) — 687 citations
• A General Agnostic Active Learning Algorithm (2007) — 334 citations
• Online Learning of Non-stationary Sequences (2003) — 61 citations