most citedLearning Humanoid Robot Motions Through Deep Neural Networks

8 citations · 11 across the 3 of their papers we have counts for

collaborators

5 papers

cs.LG2020

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…

cs.LG20193 cited

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…

cs.IR2019

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…

cs.IR2019

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…

cs.AI20198 cited

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…