32 citations · 53 across the 6 of their papers we have counts for
8 papers
Contrastive Training Improves Zero-Shot Classification of Semi-structured Documents
Muhammad Khalifa, Yogarshi Vyas, Shuai Wang +3
We investigate semi-structured document classification in a zero-shot setting. Classification of semi-structured documents is more challenging than that of standard unstructured do…
Label Semantics for Few Shot Named Entity Recognition
Jie Ma, Miguel Ballesteros, Srikanth Doss +4
We study the problem of few shot learning for named entity recognition. Specifically, we leverage the semantic information in the names of the labels as a way of giving the model a…
REPAINT: Knowledge Transfer in Deep Reinforcement Learning
Yunzhe Tao, Sahika Genc, Jonathan Chung +2
Accelerating learning processes for complex tasks by leveraging previously learned tasks has been one of the most challenging problems in reinforcement learning, especially when th…
Zero-Shot Reinforcement Learning with Deep Attention Convolutional Neural Networks
Sahika Genc, Sunil Mallya, Sravan Bodapati +2
Simulation-to-simulation and simulation-to-real world transfer of neural network models have been a difficult problem. To close the reality gap, prior methods to simulation-to-real…
SAVEHR: Self Attention Vector Representations for EHR based Personalized Chronic Disease Onset Prediction and Interpretability
Sunil Mallya, Marc Overhage, Sravan Bodapati +2
Chronic disease progression is emerging as an important area of investment for healthcare providers. As the quantity and richness of available clinical data continue to increase al…
DeepRacer: Educational Autonomous Racing Platform for Experimentation with Sim2Real Reinforcement Learning
Bharathan Balaji, Sunil Mallya, Sahika Genc +10
DeepRacer is a platform for end-to-end experimentation with RL and can be used to systematically investigate the key challenges in developing intelligent control systems. Using the…