Srivatsan Laxman
Artificial Intelligence · 2006–2015
A researcher in the Science corpus: 4 papers; trusts 25 researchers and is trusted by 14 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 31 citations into it; #12,008 of 35,345 by trust here, #11,490 by citations
- Information Systems — 21 citations into it; #2,869 of 8,771 by trust here, #1,933 by citations
- Privacy & Security — 13 citations into it; #341 of 709 by trust here, #361 by citations
- Statistics and Probability — 9 citations into it
- Computational Theory and Mathematics — 8 citations into it; #11,499 of 12,182 by trust here, #9,804 by citations
- Management Science and Operations Research — 8 citations into it; #4,657 of 11,946 by trust here, #2,472 by citations
- Sociology and Political Science — 7 citations into it
- Algorithms & Complexity — 6 citations into it
Whom Srivatsan Laxman trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Rakesh Agrawal
- Richard S. Sutton
- Lawrence R. Rabiner
- David Ruppert
- Jiawei Han
- Jianyong Wang
- Eamonn J. Keogh
- David J. Hand
- Xifeng Yan
- Frank McSherry
Who trusts Srivatsan Laxman overall
- Aleksandra Korolova
- Luca Bonomi
- Indrė Žliobaitė
- Kamalika Chaudhuri
- Stephen E. Fienberg
- Caroline Uhler
- Daniel Kifer
- Aleksandra B. Slavkovic
- Parisa Rashidi
- Jun Zhang
Papers from Srivatsan Laxman's perspective
Ordered by how strongly the researchers Srivatsan Laxman 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
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- Pattern classification and scene analysis
Their papers
- Discovering frequent patterns in sensitive data (2010) — 284 citations
- A survey of temporal data mining (2006) — 375 citations
- Discovering and understanding word level user intent in Web search queries (2015) — 27 citations
- Noiseless Database Privacy (2011) — 102 citations