523 citations · 643 across the 14 of their papers we have counts for
3 papers · 1 filter
Metric Learning from Imbalanced Data
Léo Gautheron, Emilie Morvant, Amaury Habrard +1
A key element of any machine learning algorithm is the use of a function that measures the dis/similarity between data points. Given a task, such a function can be optimized with a…
An Adjusted Nearest Neighbor Algorithm Maximizing the F-Measure from Imbalanced Data
Rémi Viola, Rémi Emonet, Amaury Habrard +3
In this paper, we address the challenging problem of learning from imbalanced data using a Nearest-Neighbor (NN) algorithm. In this setting, the minority examples typically belong…
Learning Landmark-Based Ensembles with Random Fourier Features and Gradient Boosting
Léo Gautheron, Pascal Germain, Amaury Habrard +3
We propose a Gradient Boosting algorithm for learning an ensemble of kernel functions adapted to the task at hand. Unlike state-of-the-art Multiple Kernel Learning techniques that…