John Guiver

Artificial Intelligence · 2008–2009

A researcher in the Science corpus: 2 papers; trusts 10 researchers and is trusted by 14 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 9 citations into it; #12,656 of 35,345 by trust here, #16,771 by citations
• Information Systems — 9 citations into it; #2,318 of 8,771 by trust here, #3,098 by citations
• Information Retrieval & Search — 6 citations into it

Whom John Guiver trusts overall

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

1. Tom Minka
2. David R. Hunter
3. Ralf Herbrich
4. C. Burges
5. Koby Crammer
6. Kalervo Järvelin
7. Wei Chu
8. Thore Graepel
9. Tie-Yan Liu
10. Zhe Cao

Who trusts John Guiver overall

1. Hang Li
2. Bruce E. Hajek
3. Olivier Chapelle
4. Tie-Yan Liu
5. Alexandre Gilotte
6. Yang Liu
7. Clément Calauzènes
8. Tao Qin
9. Nicolas Usunier
10. Sourav Chatterjee

Papers from John Guiver's perspective

Ordered by how strongly the researchers John Guiver trusts endorse each paper. Same corpus, a different order for every researcher.

1. Pranking with Ranking (Neural Information Processing Systems)
2. ImageNet classification with deep convolutional neural networks
3. IR evaluation methods for retrieving highly relevant documents
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Learning to rank using gradient descent
6. Learning to Rank with Nonsmooth Cost Functions
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Gradient-based learning applied to document recognition
9. Long Short-Term Memory
10. Learning to rank: from pairwise approach to listwise approach

Their papers

• SoftRank: optimizing non-smooth rank metrics (2008) — 402 citations
• Bayesian inference for Plackett-Luce ranking models (2009) — 207 citations