3 papers
cs.LG2020
Identifying Causal-Effect Inference Failure with Uncertainty-Aware Models
Andrew Jesson, Sören Mindermann, Uri Shalit +1
Recommending the best course of action for an individual is a major application of individual-level causal effect estimation. This application is often needed in safety-critical do…
cs.CV2018
CASED: Curriculum Adaptive Sampling for Extreme Data Imbalance
Andrew Jesson, Nicolas Guizard, Sina Hamidi Ghalehjegh +3
We introduce CASED, a novel curriculum sampling algorithm that facilitates the optimization of deep learning segmentation or detection models on data sets with extreme class imbala…
cs.LG2018
On the Importance of Attention in Meta-Learning for Few-Shot Text Classification
Xiang Jiang, Mohammad Havaei, Gabriel Chartrand +5
Current deep learning based text classification methods are limited by their ability to achieve fast learning and generalization when the data is scarce. We address this problem by…