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Conclusion
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Classroom Contents
Learning From Ranks, Learning to Rank - Jean-Philippe Vert, Google Brain
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- 1 Intro
- 2 Differentiable programming
- 3 Beyond images and strings
- 4 What if inputs or outputs are permutations?
- 5 Examples
- 6 Goals
- 7 Permutations as inputs
- 8 SUQUAN embedding (Le Morvan and Vert, 2017)
- 9 Supervised ON (SUQUAN)
- 10 Experiments: CIFAR-10
- 11 Limits of the SUQUAN embedding
- 12 The Kendall embedding (Jiao and Vert, 2015, 2017)
- 13 Geometry of the embedding
- 14 Kendall and Mallows kernels
- 15 Applications
- 16 Remark
- 17 Permutations as intermediate / output?
- 18 Optimal transport (OT)
- 19 Differentiable permutation matrix
- 20 Differentiable sort and rank
- 21 Soft quantization and soft quantiles
- 22 Application: soft top-k loss
- 23 Application: learning to sort
- 24 Conclusion
