Bilegsaikhan Naidan
Information Retrieval & Search · 2013–2015
A researcher in the Science corpus: 4 papers; trusts 29 researchers and is trusted by 12 researchers here, as inferred from the citation graph.
Subfields
- Information Retrieval & Search — 26 citations into it; #907 of 1,022 by trust here, #886 by citations
- Computer Vision and Pattern Recognition — 22 citations into it; #7,347 of 21,575 by trust here, #14,822 by citations
- Signal Processing — 21 citations into it; #4,217 of 7,572 by trust here, #6,083 by citations
- Artificial Intelligence — 13 citations into it; #13,398 of 35,345 by trust here, #27,551 by citations
- Algorithms & Complexity — 8 citations into it; #475 of 516 by trust here, #407 by citations
- Computer Graphics and Computer-Aided Design — 8 citations into it
Whom Bilegsaikhan Naidan trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Edgar Chávez
- Hanan Samet
- Christian Beecks
- Leonid Boytsov
- Radim Rehurek
- Sariel Har-Peled
- Eric Sadit Tellez
- Gonzalo Navarro
- Yury Malkov
- David M. Blei
Who trusts Bilegsaikhan Naidan overall
- Yury Malkov
- Alexander Ponomarenko
- Dmitry A. Yashunin
- Ben Harwood
- Leonid Boytsov
- Yu A. Malkov
- Tom Drummond
- Wen Li
- Pasquale Minervini
- N. Avrelin
Papers from Bilegsaikhan Naidan's perspective
Ordered by how strongly the researchers Bilegsaikhan Naidan 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)
- ImageNet Large Scale Visual Recognition Challenge
- Distinctive Image Features from Scale-Invariant Keypoints
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- Attention is All you Need (Neural Information Processing Systems)
Their papers
- Engineering Efficient and Effective Non-metric Space Library (2013) — 130 citations
- Permutation Search Methods are Efficient, Yet Faster Search is Possible (2015) — 59 citations
- Comparative Analysis of Data Structures for Approximate Nearest Neighbor Search (2014) — 26 citations
- Learning to Prune in Metric and Non-Metric Spaces (2013) — 22 citations