S. Chawla
Artificial Intelligence · 2001–2019
A researcher in the Science corpus: 9 papers; trusts 13 researchers and is trusted by 82 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 35 citations into it; #2,503 of 35,345 by trust here, #4,860 by citations
- Computational Theory and Mathematics — 13 citations into it; #10,127 of 12,182 by trust here, #7,142 by citations
- Information Systems — 13 citations into it
- Management Science and Operations Research — 12 citations into it; #3,715 of 11,946 by trust here, #1,613 by citations
- Privacy & Security — 11 citations into it
- Marketing — 6 citations into it; #5,088 of 6,289 by trust here, #5,673 by citations
- Optimization & Training — 6 citations into it
Whom S. Chawla trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Latanya Sweeney
- Frank McSherry
- Roger B. Myerson
- Cynthia Dwork
- Alexandre V. Evfimievski
- William I. Gasarch
- Irit Dinur
- Kobbi Nissim
- Jason D. Hartline
- Michael Kearns
Who trusts S. Chawla overall
- Cynthia Dwork
- Lalitha Sankar
- Zhi-Hua Zhou
- Eliav Buchnik
- Xiaojin Zhu
- Charu C. Aggarwal
- Mikhail Belkin
- Robert D. Kleinberg
- S. Rajagopalan
- Ming Li
Papers from S. Chawla's perspective
Ordered by how strongly the researchers S. Chawla trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Security-control methods for statistical databases: a comparative study
- On the design and quantification of privacy preserving data mining algorithms
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Privacy Preserving Data Mining
- Reinforcement Learning: An Introduction
- Revealing information while preserving privacy
Their papers
- Learning from Labeled and Unlabeled Data using Graph Mincuts (2001) — 1,115 citations
- Toward Privacy in Public Databases (2005) — 325 citations
- Correlation Clustering (2002) — 407 citations
- Multi-parameter mechanism design and sequential posted pricing (2010) — 548 citations
- Algorithmic pricing via virtual valuations (2007) — 323 citations
- Themis: Fair and Efficient GPU Cluster Scheduling for Machine Learning Workloads (2019) — 249 citations
- On Privacy-Preserving Histograms (2005) — 28 citations
- On the Utility of Privacy-Preserving Histograms (2004) — 29 citations
- Approximation algorithms for orienteering and discounted-reward TSP (2003) — 312 citations