151 citations · 542 across the 33 of their papers we have counts for
5 papers · 1 filter
Overcoming Catastrophic Forgetting by Soft Parameter Pruning
Jian Peng, Jiang Hao, Zhuo Li +5
Catastrophic forgetting is a challenge issue in continual learning when a deep neural network forgets the knowledge acquired from the former task after learning on subsequent tasks…
emrQA: A Large Corpus for Question Answering on Electronic Medical Records
Anusri Pampari, Preethi Raghavan, Jennifer Liang +1
We propose a novel methodology to generate domain-specific large-scale question answering (QA) datasets by re-purposing existing annotations for other NLP tasks. We demonstrate an…
Off-Policy Evaluation and Learning from Logged Bandit Feedback: Error Reduction via Surrogate Policy
Yuan Xie, Boyi Liu, Qiang Liu +3
When learning from a batch of logged bandit feedback, the discrepancy between the policy to be learned and the off-policy training data imposes statistical and computational challe…
Efficient Contextualized Representation: Language Model Pruning for Sequence Labeling
Liyuan Liu, Xiang Ren, Jingbo Shang +2
Many efforts have been made to facilitate natural language processing tasks with pre-trained language models (LMs), and brought significant improvements to various applications. To…
The Importance of Norm Regularization in Linear Graph Embedding: Theoretical Analysis and Empirical Demonstration
Yihan Gao, Chao Zhang, Jian Peng +1
Learning distributed representations for nodes in graphs is a crucial primitive in network analysis with a wide spectrum of applications. Linear graph embedding methods learn such…