110 citations · 227 across the 6 of their papers we have counts for
6 papers
Hybrid Session-based News Recommendation using Recurrent Neural Networks
Gabriel de Souza P. Moreira, Dietmar Jannach, Adilson Marques da Cunha
We describe a hybrid meta-architecture -- the CHAMELEON -- for session-based news recommendation that is able to leverage a variety of information types using Recurrent Neural Netw…
Bottom-Up Meta-Policy Search
Luckeciano C. Melo, Marcos R. O. A. Maximo, Adilson Marques da Cunha
Despite of the recent progress in agents that learn through interaction, there are several challenges in terms of sample efficiency and generalization across unseen behaviors durin…
On the Importance of News Content Representation in Hybrid Neural Session-based Recommender Systems
Gabriel de Souza P. Moreira, Dietmar Jannach, Adilson Marques da Cunha
News recommender systems are designed to surface relevant information for online readers by personalizing their user experiences. A particular problem in that context is that onlin…
Contextual Hybrid Session-based News Recommendation with Recurrent Neural Networks
Gabriel de Souza Pereira Moreira, Dietmar Jannach, Adilson Marques da Cunha
Recommender systems help users deal with information overload by providing tailored item suggestions to them. The recommendation of news is often considered to be challenging, sinc…
Learning Humanoid Robot Motions Through Deep Neural Networks
Luckeciano Carvalho Melo, Marcos Ricardo Omena Albuquerque Maximo, Adilson Marques da Cunha
Controlling a high degrees of freedom humanoid robot is acknowledged as one of the hardest problems in Robotics. Due to the lack of mathematical models, an approach frequently empl…
News Session-Based Recommendations using Deep Neural Networks
Gabriel de Souza P. Moreira, Felipe Ferreira, Adilson Marques da Cunha
News recommender systems are aimed to personalize users experiences and help them to discover relevant articles from a large and dynamic search space. Therefore, news domain is a c…