Yann Chevaleyre

Artificial Intelligence · 2004–2018

A researcher in the Science corpus: 7 papers; trusts 20 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 23 citations into it; #30,220 of 35,345 by trust here, #28,481 by citations
• Computational Theory and Mathematics — 10 citations into it
• Management Science and Operations Research — 10 citations into it
• Medical & Health AI — 10 citations into it; #188 of 239 by trust here, #236 by citations
• Computer Networks and Communications — 6 citations into it
• Statistical Learning Theory — 6 citations into it; #533 of 1,038 by trust here, #744 by citations
• Statistics and Probability — 6 citations into it; #11,290 of 12,932 by trust here, #12,077 by citations

Whom Yann Chevaleyre trusts overall

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

1. Prabhakar Raghavan
2. Cynthia Rudin
3. Berk Ustun
4. Vincent Conitzer
5. Geoffrey G. Towell
6. David P. Williamson
7. Fulton Wang
8. Hervé Moulin
9. H. Nader
10. D. Golovin

Who trusts Yann Chevaleyre overall

1. Berk Ustun
2. Cynthia Rudin
3. Nataliya Sokolovska
4. Jean-Daniel Zucker
5. Emilio Carrizosa
6. Tanguy Urvoy
7. Róbert Istvan Busa-Fekete
8. Amaya Nogales-Gómez
9. Yehuda Elmaliach
10. Tim Miller

Papers from Yann Chevaleyre's perspective

Ordered by how strongly the researchers Yann Chevaleyre 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. Regression Shrinkage and Selection via the Lasso
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. The Nature of Statistical Learning Theory
8. Learning Multiple Layers of Features from Tiny Images
9. Attention is All you Need (Neural Information Processing Systems)
10. GENERATIVE ADVERSARIAL NETS

Their papers

• The fused lasso penalty for learning interpretable medical scoring systems (2017) — 10 citations
• A Short Introduction to Computational Social Choice (2007) — 307 citations
• A Provable Algorithm for Learning Interpretable Scoring Systems (2018) — 21 citations
• Experimental analysis of new algorithms for learning ternary classifiers (2015)
• Rounding Methods for Discrete Linear Classification (2013) — 24 citations
• Issues in Multiagent Resource Allocation (2006) — 592 citations
• Theoretical analysis of the multi-agent patrolling problem (2004) — 309 citations