Milind Kulkarni

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 12 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 23 citations into it
• Federated & Distributed Learning — 12 citations into it
• Meta & Continual Learning — 6 citations into it
• Optimization & Training — 6 citations into it

Whom Milind Kulkarni trusts overall

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

1. H. Brendan McMahan
2. Chelsea Finn
3. Alex Nichol
4. Geoffrey E. Hinton
5. Alireza Fallah
6. Yishay Mansour
7. Yihan Jiang
8. Pieter Abbeel
9. Sergey Levine
10. Kangkang Wang

Who trusts Milind Kulkarni overall

1. Yutao Huang

Papers from Milind Kulkarni's perspective

Ordered by how strongly the researchers Milind Kulkarni 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. Gradient-based learning applied to document recognition
4. Long Short-Term Memory
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Learning Multiple Layers of Features from Tiny Images
7. Distilling the Knowledge in a Neural Network (arXiv.org)
8. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
9. Attention is All you Need (Neural Information Processing Systems)
10. ImageNet: A large-scale hierarchical image database

Their papers

• Survey of Personalization Techniques for Federated Learning (2020) — 394 citations