1 citations · 2 across the 6 of their papers we have counts for
12 papers
Learning primal-dual sparse kernel machines
Riikka Huusari, Sahely Bhadra, Cécile Capponi +2
Traditionally, kernel methods rely on the representer theorem which states that the solution to a learning problem is obtained as a linear combination of the data mapped into the r…
Implicit Regularization in Deep Tensor Factorization
Paolo Milanesi, Hachem Kadri, Stéphane Ayache +1
Attempts of studying implicit regularization associated to gradient descent (GD) have identified matrix completion as a suitable test-bed. Late findings suggest that this phenomeno…
Entangled Kernels -- Beyond Separability
Riikka Huusari, Hachem Kadri
We consider the problem of operator-valued kernel learning and investigate the possibility of going beyond the well-known separable kernels. Borrowing tools and concepts from the f…
Partial Trace Regression and Low-Rank Kraus Decomposition
Hachem Kadri, Stéphane Ayache, Riikka Huusari +2
The trace regression model, a direct extension of the well-studied linear regression model, allows one to map matrices to real-valued outputs. We here introduce an even more genera…
Mapping individual differences in cortical architecture using multi-view representation learning
Akrem Sellami, François-Xavier Dupé, Bastien Cagna +4
In neuroscience, understanding inter-individual differences has recently emerged as a major challenge, for which functional magnetic resonance imaging (fMRI) has proven invaluable.…
Quantum Bandits
Balthazar Casalé, Giuseppe Di Molfetta, Hachem Kadri +1
We consider the quantum version of the bandit problem known as {\em best arm identification} (BAI). We first propose a quantum modeling of the BAI problem, which assumes that both…