Jalaj Upadhyay
Artificial Intelligence · 2013–2017
A researcher in the Science corpus: 2 papers; trusts 47 researchers and is trusted by 8 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 39 citations into it; #19,024 of 35,345 by trust here, #17,776 by citations
- Privacy & Security — 25 citations into it
- Computational Theory and Mathematics — 15 citations into it
- Statistics and Probability — 11 citations into it
- Computational Mechanics — 9 citations into it
- Optimization & Training — 8 citations into it
- Algorithms & Complexity — 5 citations into it
- Discrete Mathematics and Combinatorics — 5 citations into it
Whom Jalaj Upadhyay trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Daniel A. Spielman
- Cynthia Dwork
- Frank McSherry
- Aaron Roth
- Anupam Gupta
- M. Kapralov
- Nir Ailon
- Raphael Yuster
- Kunal Talwar
- Kobbi Nissim
Who trusts Jalaj Upadhyay overall
Papers from Jalaj Upadhyay's perspective
Ordered by how strongly the researchers Jalaj Upadhyay trusts endorse each paper. Same corpus, a different order for every researcher.
- Calibrating Noise to Sensitivity in Private Data Analysis
- Efficient noise-tolerant learning from statistical queries
- ImageNet classification with deep convolutional neural networks
- Gradient-based learning applied to document recognition
- Learning Multiple Layers of Features from Tiny Images
- Differential Privacy
- Differentially private recommender systems: building privacy into the net
- Differentially Private Empirical Risk Minimization
- Revealing information while preserving privacy
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
Their papers
- Is Interaction Necessary for Distributed Private Learning? (2017) — 160 citations
- Random Projections, Graph Sparsification, and Differential Privacy (2013) — 37 citations