Pavan Kumar Mallapragada

Artificial Intelligence · 2009

A researcher in the Science corpus: 2 papers; trusts 9 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 15 citations into it; #30,817 of 35,345 by trust here, #25,040 by citations
• Statistical Learning Theory — 5 citations into it
• Optimization & Training — 5 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Pavan Kumar Mallapragada trusts overall

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

1. Thorsten Joachims
2. Olivier Chapelle
3. Vladimir Naumovich Vapnik
4. Yoav Freund
5. Nello Cristianini
6. Avrim Blum
7. Xiaojin Zhu
8. Martin Szummer
9. Ian H. Witten
10. Robert E. Schapire

Who trusts Pavan Kumar Mallapragada overall

1. Jesper E. van Engelen
2. Helmut Grabner
3. Holger H. Hoos
4. Christian Leistner
5. Yuncheng Li
6. Ziming Zhang
7. Hsiang-Fu Yu

Papers from Pavan Kumar Mallapragada's perspective

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

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

Their papers

• Efficient multi-label ranking for multi-class learning: Application to object recognition (2009) — 51 citations
• SemiBoost: Boosting for Semi-Supervised Learning (2009) — 360 citations