Balamurugan Palaniappan
Optimization & Training · 2011–2016
A researcher in the Science corpus: 2 papers; trusts 34 researchers and is trusted by 31 researchers here, as inferred from the citation graph.
Subfields
- Optimization & Training — 28 citations into it; #610 of 2,601 by trust here, #1,661 by citations
- Artificial Intelligence — 18 citations into it; #5,743 of 35,345 by trust here, #19,018 by citations
- Computational Mechanics — 7 citations into it
- Computational Theory and Mathematics — 7 citations into it
- Computer Vision and Pattern Recognition — 5 citations into it
- Mathematical Optimization — 5 citations into it
- Statistics and Probability — 5 citations into it; #1,893 of 12,932 by trust here, #5,126 by citations
Whom Balamurugan Palaniappan trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Thorsten Joachims
- Tong Zhang
- Francis R. Bach
- Rie Johnson
- Antonin Chambolle
- Heinz H. Bauschke
- Aaron Defazio
- Yuchen Zhang
- George H.-G. Chen
- Ernest K. Ryu
Who trusts Balamurugan Palaniappan overall
- Gauthier Gidel
- Tianbao Yang
- Hugo Berard
- Simon Lacoste-Julien
- Waïss Azizian
- Nicolas Loizou
- Luo Luo
- Junchi Yang
- Tatjana Chavdarova
- Qihang Lin
Papers from Balamurugan Palaniappan's perspective
Ordered by how strongly the researchers Balamurugan Palaniappan trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Stochastic Variance Reduction Methods for Saddle-Point Problems (2016) — 225 citations
- A Sequential Dual Method for Structural SVMs (2011) — 27 citations