collaborators

5 papers

cs.LG2019

MarlRank: Multi-agent Reinforced Learning to Rank

Shihao Zou, Zhonghua Li, Mohammad Akbari +2

When estimating the relevancy between a query and a document, ranking models largely neglect the mutual information among documents. A common wisdom is that if two documents are si…

stat.ML2019

Using Contextual Information to Improve Blood Glucose Prediction

Mohammad Akbari, Rumi Chunara

Blood glucose value prediction is an important task in diabetes management. While it is reported that glucose concentration is sensitive to social context such as mood, physical ac…

cs.SI2018

From the User to the Medium: Neural Profiling Across Web Communities

Mohammad Akbari, Kunal Relia, Anas Elghafari +1

Online communities provide a unique way for individuals to access information from those in similar circumstances, which can be critical for health conditions that require daily an…

cs.CL2018

Named Entity Disambiguation using Deep Learning on Graphs

Alberto Cetoli, Mohammad Akbari, Stefano Bragaglia +2

We tackle \ac{NED} by comparing entities in short sentences with \wikidata{} graphs. Creating a context vector from graphs through deep learning is a challenging problem that has n…

cs.SI2018

Socio-spatial Self-organizing Maps: Using Social Media to Assess Relevant Geographies for Exposure to Social Processes

Kunal Relia, Mohammad Akbari, Dustin Duncan +1

Social media offers a unique window into attitudes like racism and homophobia, exposure to which are important, hard to measure and understudied social determinants of health. Howe…