62 citations · 95 across the 11 of their papers we have counts for
12 papers
Maximum Entropy Semi-Supervised Inverse Reinforcement Learning
Julien Audiffren, Michal Valko, Alessandro Lazaric +1
A popular approach to apprenticeship learning (AL) is to formulate it as an inverse reinforcement learning (IRL) problem. The MaxEnt-IRL algorithm successfully integrates the maxim…
Tensor Convolutional Sparse Coding with Low-Rank activations, an application to EEG analysis
Pierre Humbert, Laurent Oudre, Nivolas Vayatis +1
Recently, there has been growing interest in the analysis of spectrograms of ElectroEncephaloGram (EEG), particularly to study the neural correlates of (un)-consciousness during Ge…
Fusing Vector Space Models for Domain-Specific Applications
Laura Rettig, Julien Audiffren, Philippe Cudré-Mauroux
We address the problem of tuning word embeddings for specific use cases and domains. We propose a new method that automatically combines multiple domain-specific embeddings, select…
Multivariate Convolutional Sparse Coding with Low Rank Tensor
Pierre Humbert, Julien Audiffren, Laurent Oudre +1
This paper introduces a new multivariate convolutional sparse coding based on tensor algebra with a general model enforcing both element-wise sparsity and low-rankness of the activ…
Post Training in Deep Learning with Last Kernel
Thomas Moreau, Julien Audiffren
One of the main challenges of deep learning methods is the choice of an appropriate training strategy. In particular, additional steps, such as unsupervised pre-training, have been…
Decoy Bandits Dueling on a Poset
Julien Audiffren, Ralaivola Liva
We adress the problem of dueling bandits defined on partially ordered sets, or posets. In this setting, arms may not be comparable, and there may be several (incomparable) optimal…