activity
20202022
most citedTwo Step Joint Model for Drug Drug Interaction Extraction

6 citations · 17 across the 6 of their papers we have counts for

collaborators

6 papers

cs.AI20225 cited

Process Knowledge-infused Learning for Suicidality Assessment on Social Media

Kaushik Roy, Manas Gaur, Qi Zhang +1

Improving the performance and natural language explanations of deep learning algorithms is a priority for adoption by humans in the real world. In several domains, such as healthca…

cs.LG20221 cited

A Multi-agent Reinforcement Learning Approach for Efficient Client Selection in Federated Learning

Sai Qian Zhang, Jieyu Lin, Qi Zhang

Federated learning (FL) is a training technique that enables client devices to jointly learn a shared model by aggregating locally-computed models without exposing their raw data.…

cs.CL20211 cited

MeDiaQA: A Question Answering Dataset on Medical Dialogues

Huqun Suri, Qi Zhang, Wenhua Huo +2

In this paper, we introduce MeDiaQA, a novel question answering(QA) dataset, which constructed on real online Medical Dialogues. It contains 22k multiple-choice questions annotated…

cs.LG2021

Knowledge Infused Policy Gradients with Upper Confidence Bound for Relational Bandits

Kaushik Roy, Qi Zhang, Manas Gaur +1

Contextual Bandits find important use cases in various real-life scenarios such as online advertising, recommendation systems, healthcare, etc. However, most of the algorithms use…

cs.AI20214 cited

Knowledge Infused Policy Gradients for Adaptive Pandemic Control

Kaushik Roy, Qi Zhang, Manas Gaur +1

COVID-19 has impacted nations differently based on their policy implementations. The effective policy requires taking into account public information and adaptability to new knowle…

cs.CL20206 cited

Two Step Joint Model for Drug Drug Interaction Extraction

Siliang Tang, Qi Zhang, Tianpeng Zheng +7

When patients need to take medicine, particularly taking more than one kind of drug simultaneously, they should be alarmed that there possibly exists drug-drug interaction. Interac…