Optimizing expensive to evaluate black-box functions over an input space consisting of all
permutations of d objects is an important problem with many real-world applications. For …

Algorithms that utilize bandit feedback to optimize top-k recommendations are vital for online
marketplaces, search engines, and content platforms. However, the combinatorial nature of …

Given a profile of ranking lists over a finite set of alternatives, probabilistic social choice
seeks to select a probability function over the alternatives on the basis of the pairwise …

Many real-world scientific and engineering problems can be formulated as instances of goal-
driven adaptive experimental design, wherein candidate experiments are chosen …

Many algorithms for ranked data become computationally intractable as the number of
objects grows due to the complex geometric structure induced by rankings. An additional …

Learning from ranks, learning to rank Page 1 Learning from ranks, learning to rank Jean-Philippe
Vert Page 2 ML https://codeburst.io/machine-learning-243cc92247a1 Page 3 Beyond images …

The possibility to collect large amounts of genomic data from cancer patients paves the way
to automatic patient stratification and improved prediction of survival, risk of relapse or …

Machine learning on the symmetric group Page 1 Machine learning on the symmetric group
Jean-Philippe Vert Page 2 ML Page 3 ML Page 4 ML Page 5 ML Page 6 What if inputs are …

Learning with permutations Page 1 Learning with permutations Jean-Philippe Vert
Takeuchi Laboratory, Nagoya Institute of Technology, Aug 1, 2018 Page 2 Motivations …