715 citations · 1.4k across the 35 of their papers we have counts for
4 papers · 1 filter
Learning to Score Behaviors for Guided Policy Optimization
Aldo Pacchiano, Jack Parker-Holder, Yunhao Tang +3
We introduce a new approach for comparing reinforcement learning policies, using Wasserstein distances (WDs) in a newly defined latent behavioral space. We show that by utilizing t…
LdSM: Logarithm-depth Streaming Multi-label Decision Trees
Maryam Majzoubi, Anna Choromanska
We consider multi-label classification where the goal is to annotate each data point with the most relevant of labels from an extremely large label set. Efficient…
Leader Stochastic Gradient Descent for Distributed Training of Deep Learning Models: Extension
Yunfei Teng, Wenbo Gao, Francois Chalus +3
We consider distributed optimization under communication constraints for training deep learning models. We propose a new algorithm, whose parameter updates rely on two forces: a re…
Towards Automated Melanoma Detection with Deep Learning: Data Purification and Augmentation
Devansh Bisla, Anna Choromanska, Jennifer A. Stein +2
Melanoma is one of the ten most common cancers in the US. Early detection is crucial for survival, but often the cancer is diagnosed in the fatal stage. Deep learning has the poten…