5 citations · 10 across the 5 of their papers we have counts for
5 papers
Distributed Ensembles of Reinforcement Learning Agents for Electricity Control
Pierrick Pochelu, Serge G. Petiton, Bruno Conche
Deep Reinforcement Learning (or just "RL") is gaining popularity for industrial and research applications. However, it still suffers from some key limits slowing down its widesprea…
Weakly Supervised Faster-RCNN+FPN to classify animals in camera trap images
Pierrick Pochelu, Clara Erard, Philippe Cordier +2
Camera traps have revolutionized the animal research of many species that were previously nearly impossible to observe due to their habitat or behavior. They are cameras generally…
An efficient and flexible inference system for serving heterogeneous ensembles of deep neural networks
Pierrick Pochelu, Serge G. Petiton, Bruno Conche
Ensembles of Deep Neural Networks (DNNs) have achieved qualitative predictions but they are computing and memory intensive. Therefore, the demand is growing to make them answer a h…
A Deep Neural Networks ensemble workflow from hyperparameter search to inference leveraging GPU clusters
Pierrick Pochelu, Serge G. Petiton, Bruno Conche
Automated Machine Learning with ensembling (or AutoML with ensembling) seeks to automatically build ensembles of Deep Neural Networks (DNNs) to achieve qualitative predictions. Ens…
Reliable multicast fault tolerant MPI in the Grid environment
Benoit Hudzia, Serge Petiton
Grid environments have recently been developed with low stretch and overheads that increase with the logarithm of the number of nodes in the system. Getting and sending data to/fro…