70 citations · 198 across the 23 of their papers we have counts for
4 papers · 1 filter
From Cutting Planes Algorithms to Compression Schemes and Active Learning
Liva Ralaivola, Ugo Louche
Cutting-plane methods are well-studied localization(and optimization) algorithms. We show that they provide a natural framework to perform machinelearning ---and not just to solve…
Greedy methods, randomization approaches and multi-arm bandit algorithms for efficient sparsity-constrained optimization
A Rakotomamonjy, S Koço, Liva Ralaivola
Several sparsity-constrained algorithms such as Orthogonal Matching Pursuit or the Frank-Wolfe algorithm with sparsity constraints work by iteratively selecting a novel atom to add…
Unconfused ultraconservative multiclass algorithms
Ugo Louche, Liva Ralaivola
We tackle the problem of learning linear classifiers from noisy datasets in a multiclass setting. The two-class version of this problem was studied a few years ago where the propos…
On Generalizing the C-Bound to the Multiclass and Multi-label Settings
Francois Laviolette, Emilie Morvant, Liva Ralaivola +1
The C-bound, introduced in Lacasse et al., gives a tight upper bound on the risk of a binary majority vote classifier. In this work, we present a first step towards extending this…