20 citations · 29 across the 2 of their papers we have counts for
2 papers
cs.LG2019★ 20 cited
Learning latent state representation for speeding up exploration
Giulia Vezzani, Abhishek Gupta, Lorenzo Natale +1
Exploration is an extremely challenging problem in reinforcement learning, especially in high dimensional state and action spaces and when only sparse rewards are available. Effect…
cs.RO2015★ 9 cited
Real-world Object Recognition with Off-the-shelf Deep Conv Nets: How Many Objects can iCub Learn?
Giulia Pasquale, Carlo Ciliberto, Francesca Odone +2
The ability to visually recognize objects is a fundamental skill for robotics systems. Indeed, a large variety of tasks involving manipulation, navigation or interaction with other…