Christos Boutsidis

Artificial Intelligence · 2008–2015

A researcher in the Science corpus: 5 papers; trusts 48 researchers and is trusted by 49 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 29 citations into it; #9,116 of 35,345 by trust here, #15,236 by citations
• Computational Mechanics — 22 citations into it; #7,764 of 10,001 by trust here, #6,041 by citations
• Computational Theory and Mathematics — 20 citations into it; #990 of 12,182 by trust here, #2,931 by citations
• Computer Vision and Pattern Recognition — 20 citations into it; #10,113 of 21,575 by trust here, #16,787 by citations
• Molecular Biology — 7 citations into it; #5,501 of 17,773 by trust here, #14,509 by citations
• Statistics and Probability — 6 citations into it; #10,210 of 12,932 by trust here, #6,853 by citations
• Computational Mathematics — 5 citations into it; #112 of 612 by trust here, #350 by citations

Whom Christos Boutsidis trusts overall

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

1. Inderjit S. Dhillon
2. Kenneth L. Clarkson
3. David P. Woodruff
4. Petros Drineas
5. Tamás Sarlós
6. Chris H. Q. Ding
7. Edo Liberty
8. Daniel D. Lee
9. Timothy A. Davis
10. Michael W. Mahoney

Who trusts Christos Boutsidis overall

1. David P. Woodruff
2. Seonguk Park
3. Stephen A. Vavasis
4. Deng Cai
5. Yu-Xiong Wang
6. Marinka Zitnik
7. Homer F. Walker
8. Renaud Gaujoux
9. Nicolas Gillis
10. Alex Gittens

Papers from Christos Boutsidis's perspective

Ordered by how strongly the researchers Christos Boutsidis 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. 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. Going deeper with convolutions
10. Et al

Their papers

• A Randomized Algorithm for Approximating the Log Determinant of a Symmetric Positive Definite Matrix (2015) — 82 citations
• An improved approximation algorithm for the column subset selection problem (2008) — 421 citations
• SVD based initialization: A head start for nonnegative matrix factorization (2008) — 739 citations
• Unsupervised feature selection for principal components analysis (2008) — 136 citations
• Optimal principal component analysis in distributed and streaming models (2015) — 124 citations