Amit Deshpande
Artificial Intelligence · with Rademacher · 2006–2018
A researcher in the Science corpus: 4 papers; trusts 20 researchers and is trusted by 19 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 17 citations into it; #11,284 of 35,345 by trust here, #12,244 by citations
- Signal Processing — 9 citations into it; #6,655 of 7,572 by trust here, #3,784 by citations
- Computer Vision and Pattern Recognition — 8 citations into it; #8,717 of 21,575 by trust here, #12,992 by citations
- Computational Theory and Mathematics — 7 citations into it; #5,887 of 12,182 by trust here, #7,851 by citations
- Computational Mechanics — 6 citations into it; #3,259 of 10,001 by trust here, #4,315 by citations
- Statistics and Probability — 6 citations into it; #6,571 of 12,932 by trust here, #8,279 by citations
Whom Amit Deshpande trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Petros Drineas
- Sergei A. Goreinov
- Avner Magen
- Sariel Har-Peled
- Michael W. Mahoney
- Christos Boutsidis
- Frank McSherry
- Dimitris Achlioptas
- David Kempe
- Sudipto Guha
Who trusts Amit Deshpande overall
- Dan Feldman
- Petros Drineas
- David P. Woodruff
- Peter Bhlmann
- Charalampos E. Tsourakakis
- Tamás Sarlós
- Christos Boutsidis
- Maxim Sviridenko
- Kenneth L. Clarkson
- R. Kannan
Papers from Amit Deshpande's perspective
Ordered by how strongly the researchers Amit Deshpande trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Gradient-based learning applied to document recognition
- Matrix Computations
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Going deeper with convolutions
Their papers
- Efficient Volume Sampling for Row/Column Subset Selection (2010) — 215 citations
- Fair and Diverse DPP-based Data Summarization (2018) — 135 citations
- NP-hardness of Euclidean sum-of-squares clustering (2008) — 1,037 citations
- Matrix approximation and projective clustering via volume sampling (2006) — 386 citations