75 citations · 372 across the 57 of their papers we have counts for
7 papers · 1 filter
TextTubes for Detecting Curved Text in the Wild
Joël Seytre, Jon Wu, Alessandro Achille
We present a detector for curved text in natural images. We model scene text instances as tubes around their medial axes and introduce a parametrization-invariant loss function. We…
Eternal Sunshine of the Spotless Net: Selective Forgetting in Deep Networks
Aditya Golatkar, Alessandro Achille, Stefano Soatto
We explore the problem of selectively forgetting a particular subset of the data used for training a deep neural network. While the effects of the data to be forgotten can be hidde…
Toward Understanding Catastrophic Forgetting in Continual Learning
Cuong V. Nguyen, Alessandro Achille, Michael Lam +3
We study the relationship between catastrophic forgetting and properties of task sequences. In particular, given a sequence of tasks, we would like to understand which properties o…
Time Matters in Regularizing Deep Networks: Weight Decay and Data Augmentation Affect Early Learning Dynamics, Matter Little Near Convergence
Aditya Golatkar, Alessandro Achille, Stefano Soatto
Regularization is typically understood as improving generalization by altering the landscape of local extrema to which the model eventually converges. Deep neural networks (DNNs),…
Where is the Information in a Deep Neural Network?
Alessandro Achille, Giovanni Paolini, Stefano Soatto
Whatever information a deep neural network has gleaned from training data is encoded in its weights. How this information affects the response of the network to future data remains…
The Information Complexity of Learning Tasks, their Structure and their Distance
Alessandro Achille, Giovanni Paolini, Glen Mbeng +1
We introduce an asymmetric distance in the space of learning tasks, and a framework to compute their complexity. These concepts are foundational for the practice of transfer learni…