2 citations · 2 across the 2 of their papers we have counts for
3 papers
Grokking through the Lens of Minimum-Norm Interpolation
Gil Kur, Ileana Rugina, Clémentine Carla Juliette Dominé +1
Grokking shows that fitting the training data and learning the underlying signal can occur at very different stages. However, existing theories offer limited quantitative insight i…
Meta-Learning and Self-Supervised Pretraining for Real World Image Translation
Ileana Rugina, Rumen Dangovski, Mark Veillette +4
Recent advances in deep learning, in particular enabled by hardware advances and big data, have provided impressive results across a wide range of computational problems such as co…
Data-Informed Global Sparseness in Attention Mechanisms for Deep Neural Networks
Ileana Rugina, Rumen Dangovski, Li Jing +2
Attention mechanisms play a crucial role in the neural revolution of Natural Language Processing (NLP). With the growth of attention-based models, several pruning techniques have b…