V. Aggarwal
Artificial Intelligence · with Arivazhagan · 2019
A researcher in the Science corpus: 1 paper; trusts 9 researchers and is trusted by 6 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 13 citations into it; #21,733 of 35,345 by trust here, #19,873 by citations
Whom V. Aggarwal trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Who trusts V. Aggarwal overall
Papers from V. Aggarwal's perspective
Ordered by how strongly the researchers V. Aggarwal trusts endorse each paper. Same corpus, a different order for every researcher.
- Learning Multiple Layers of Features from Tiny Images
- ImageNet classification with deep convolutional neural networks
- Gradient-based learning applied to document recognition
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- ImageNet: A large-scale hierarchical image database
- Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
- Attention is All you Need (Neural Information Processing Systems)
Their papers
- Federated Learning with Personalization Layers (2019) — 1,302 citations