Balaji Krishnapuram

Artificial Intelligence · 2005–2016

A researcher in the Science corpus: 4 papers; trusts 22 researchers and is trusted by 45 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 19 citations into it; #14,905 of 35,345 by trust here, #10,942 by citations
• Probabilistic & Bayesian Methods — 10 citations into it; #360 of 1,525 by trust here, #273 by citations
• Statistical Learning Theory — 9 citations into it
• Representation & Self-Supervised Learning — 8 citations into it
• Statistics and Probability — 8 citations into it
• Computer Vision and Pattern Recognition — 7 citations into it; #9,581 of 21,575 by trust here, #7,657 by citations

Whom Balaji Krishnapuram trusts overall

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

1. Radford M. Neal
2. Matthias W. Seeger
3. Tom Minka
4. David A. McAllester
5. Dustin Boswell
6. Mário A. T. Figueiredo
7. George Eastman House
8. Michael E. Tipping
9. Peter L. Bartlett
10. Michael I. Jordan

Who trusts Balaji Krishnapuram overall

1. Jun Yu Li
2. Yu Zhang
3. Florent Perronnin
4. Jerome H. Friedman
5. Patrick Breheny
6. Pedram Ghamisi
7. Volkan Cevher
8. Kwangmoo Koh
9. Srikanth Ryali
10. Yu Zhang

Papers from Balaji Krishnapuram's perspective

Ordered by how strongly the researchers Balaji Krishnapuram trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Learning Multiple Layers of Features from Tiny Images
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Sparse multinomial logistic regression: fast algorithms and generalization bounds (2005) — 957 citations
• Bayesian multiple instance learning: automatic feature selection and inductive transfer (2008) — 160 citations
• Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (2016) — 210 citations
• Multi-Task Learning for Classification with Dirichlet Process Priors (2007) — 621 citations