Pannagadatta K. Shivaswamy
Artificial Intelligence · 2006–2015
A researcher in the Science corpus: 8 papers; trusts 66 researchers and is trusted by 10 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 55 citations into it; #12,252 of 35,345 by trust here, #17,412 by citations
- Information Systems — 26 citations into it
- Management Science and Operations Research — 26 citations into it; #3,295 of 11,946 by trust here, #7,262 by citations
- Optimization & Training — 13 citations into it
- Statistical Learning Theory — 12 citations into it
- Reinforcement Learning — 12 citations into it
- Computer Networks and Communications — 10 citations into it
- Computer Vision and Pattern Recognition — 10 citations into it
Whom Pannagadatta K. Shivaswamy trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Thorsten Joachims
- Vladimir Naumovich Vapnik
- Martin A. Zinkevich
- Yoav Freund
- Robert E. Schapire
- Yisong Yue
- Rosie Jones
- Peter Auer
- Leo Breiman
- Nicolò Cesa-Bianchi
Who trusts Pannagadatta K. Shivaswamy overall
- Huan Xu
- Ashesh Jain
- Thorsten Joachims
- Ellen R. Novoseller
- Emilio Carrizosa
- Karthik Raman
- Hyrum S. Anderson
- Shie Mannor
- Aharon Ben-Tal
- Constantine Caramanis
Papers from Pannagadatta K. Shivaswamy's perspective
Ordered by how strongly the researchers Pannagadatta K. Shivaswamy 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)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Online Structured Prediction via Coactive Learning (2012) — 66 citations
- Multi-task learning for boosting with application to web search ranking (2010) — 111 citations
- Coactive Learning (2015) — 72 citations
- Personalizing LinkedIn Feed (2015) — 41 citations
- Online learning to diversify from implicit feedback (2012) — 71 citations
- Variance Penalizing AdaBoost (2011) — 17 citations
- Empirical Bernstein Boosting (2010) — 19 citations
- Second Order Cone Programming Approaches for Handling Missing and Uncertain Data (2006) — 252 citations