Manas A. Pathak

Artificial Intelligence · 2010–2012

A researcher in the Science corpus: 4 papers; trusts 55 researchers and is trusted by 16 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 50 citations into it
• Privacy & Security — 26 citations into it; #311 of 709 by trust here, #372 by citations
• Computational Theory and Mathematics — 15 citations into it
• Safety, Robustness & Interpretability — 12 citations into it
• Computer Vision and Pattern Recognition — 7 citations into it
• Signal Processing — 7 citations into it
• Optimization & Training — 6 citations into it
• Sociology and Political Science — 6 citations into it

Whom Manas A. Pathak trusts overall

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

1. Cynthia Dwork
2. Pascal Paillier
3. Kobbi Nissim
4. Craig Gentry
5. Kamalika Chaudhuri
6. Adam D. Smith
7. Olivier Chapelle
8. Arvind Narayanan
9. Christoph Helmberg
10. Caroline Fontaine

Who trusts Manas A. Pathak overall

1. Arun Rajkumar
2. Bargav Jayaraman
3. Nicolas Papernot
4. Jinhyun So
5. Aurélien Bellet
6. Jihun Hamm
7. Ryo Yonetani
8. Prateek Jain
9. Nguyen Binh Truong
10. Bo Liu

Papers from Manas A. Pathak's perspective

Ordered by how strongly the researchers Manas A. Pathak 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. ImageNet: A large-scale hierarchical image database
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Calibrating Noise to Sensitivity in Private Data Analysis
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Long Short-Term Memory

Their papers

• Large Margin Gaussian Mixture Models with Differential Privacy (2012) — 17 citations
• Privacy-Preserving Machine Learning for Speech Processing (2012) — 20 citations
• Privacy preserving probabilistic inference with Hidden Markov Models (2011) — 50 citations
• Multiparty Differential Privacy via Aggregation of Locally Trained Classifiers (2010) — 206 citations