94 citations · 399 across the 21 of their papers we have counts for
5 papers · 1 filter
Task-Relevant Adversarial Imitation Learning
Konrad Zolna, Scott Reed, Alexander Novikov +6
We show that a critical vulnerability in adversarial imitation is the tendency of discriminator networks to learn spurious associations between visual features and expert labels. W…
Scaling data-driven robotics with reward sketching and batch reinforcement learning
Serkan Cabi, Sergio Gómez Colmenarejo, Alexander Novikov +13
We present a framework for data-driven robotics that makes use of a large dataset of recorded robot experience and scales to several tasks using learned reward functions. We show h…
The Dynamics of Handwriting Improves the Automated Diagnosis of Dysgraphia
Konrad Zolna, Thibault Asselborn, Caroline Jolly +4
Handwriting disorder (termed dysgraphia) is a far from a singular problem as nearly 8.6% of the population in France is considered dysgraphic. Moreover, research highlights the fun…
Split Batch Normalization: Improving Semi-Supervised Learning under Domain Shift
Michał Zając, Konrad Zolna, Stanisław Jastrzębski
Recent work has shown that using unlabeled data in semi-supervised learning is not always beneficial and can even hurt generalization, especially when there is a class mismatch bet…
Reinforced Imitation in Heterogeneous Action Space
Konrad Zolna, Negar Rostamzadeh, Yoshua Bengio +2
Imitation learning is an effective alternative approach to learn a policy when the reward function is sparse. In this paper, we consider a challenging setting where an agent and an…