Pratik Gajane

Artificial Intelligence · 2015–2017

A researcher in the Science corpus: 3 papers; trusts 44 researchers and is trusted by 16 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 31 citations into it; #9,963 of 35,345 by trust here, #17,110 by citations
• Management Science and Operations Research — 18 citations into it; #6,146 of 11,946 by trust here, #8,469 by citations
• Reinforcement Learning — 18 citations into it; #1,447 of 2,242 by trust here, #2,036 by citations
• Sociology and Political Science — 16 citations into it; #8,394 of 22,756 by trust here, #11,934 by citations
• AI Ethics, Fairness & Society — 11 citations into it; #214 of 494 by trust here, #308 by citations
• Safety Research — 11 citations into it; #1,950 of 5,829 by trust here, #2,985 by citations
• Safety, Robustness & Interpretability — 9 citations into it
• Computer Networks and Communications — 7 citations into it; #5,068 of 9,886 by trust here, #7,492 by citations

Whom Pratik Gajane trusts overall

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

1. S. Fukuda‐Parr
2. Indrė Žliobaitė
3. Andrea Romei
4. Salvatore Ruggieri
5. Ashwin Deshpande
6. Yisong Yue
7. E. Bonilla-Silva
8. Thorsten Joachims
9. Toon Calders
10. Masrour Zoghi

Who trusts Pratik Gajane overall

1. Aadirupa Saha
2. Aldo Pacchiano
3. Róbert Istvan Busa-Fekete
4. Julia Kreutzer
5. Chang Li
6. Carolin (Haas) Lawrence
7. Silvia Chiappa
8. Stefan Riezler
9. Luca Oneto
10. Avishek Joey Bose

Papers from Pratik Gajane's perspective

Ordered by how strongly the researchers Pratik Gajane 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. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Reinforcement Learning: An Introduction
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• A Relative Exponential Weighing Algorithm for Adversarial Utility-based Dueling Bandits (2015) — 54 citations
• On formalizing fairness in prediction with machine learning (2017) — 223 citations
• Counterfactual Learning for Machine Translation: Degeneracies and Solutions (2017) — 7 citations