192 citations · 244 across the 9 of their papers we have counts for
5 papers · 1 filter
On Hard Episodes in Meta-Learning
Samyadeep Basu, Amr Sharaf, Nicolo Fusi +1
Existing meta-learners primarily focus on improving the average task accuracy across multiple episodes. Different episodes, however, may vary in hardness and quality leading to a w…
Random Network Distillation as a Diversity Metric for Both Image and Text Generation
Liam Fowl, Micah Goldblum, Arjun Gupta +2
Generative models are increasingly able to produce remarkably high quality images and text. The community has developed numerous evaluation metrics for comparing generative models.…
Data Augmentation for Meta-Learning
Renkun Ni, Micah Goldblum, Amr Sharaf +2
Conventional image classifiers are trained by randomly sampling mini-batches of images. To achieve state-of-the-art performance, practitioners use sophisticated data augmentation s…
Active Imitation Learning with Noisy Guidance
Kianté Brantley, Amr Sharaf, Hal Daumé
Imitation learning algorithms provide state-of-the-art results on many structured prediction tasks by learning near-optimal search policies. Such algorithms assume training-time ac…
Meta-Learning for Contextual Bandit Exploration
Amr Sharaf, Hal Daumé
We describe MELEE, a meta-learning algorithm for learning a good exploration policy in the interactive contextual bandit setting. Here, an algorithm must take actions based on cont…