2 citations · 5 across the 8 of their papers we have counts for
8 papers
Ensemble Prediction of Task Affinity for Efficient Multi-Task Learning
Afiya Ayman, Ayan Mukhopadhyay, Aron Laszka
A fundamental problem in multi-task learning (MTL) is identifying groups of tasks that should be learned together. Since training MTL models for all possible combinations of tasks…
Task Grouping for Automated Multi-Task Machine Learning via Task Affinity Prediction
Afiya Ayman, Ayan Mukhopadhyay, Aron Laszka
When a number of similar tasks have to be learned simultaneously, multi-task learning (MTL) models can attain significantly higher accuracy than single-task learning (STL) models.…
Artificial Intelligence for Smart Transportation
Michael Wilbur, Amutheezan Sivagnanam, Afiya Ayman +3
There are more than 7,000 public transit agencies in the U.S. (and many more private agencies), and together, they are responsible for serving 60 billion passenger miles each year.…
The Benefits of Vulnerability Discovery and Bug Bounty Programs: Case Studies of Chromium and Firefox
Soodeh Atefi, Amutheezan Sivagnanam, Afiya Ayman +2
Recently, bug-bounty programs have gained popularity and become a significant part of the security culture of many organizations. Bug-bounty programs enable organizations to enhanc…
Impact of COVID-19 on Public Transit Accessibility and Ridership
Michael Wilbur, Afiya Ayman, Anna Ouyang +7
Public transit is central to cultivating equitable communities. Meanwhile, the novel coronavirus disease COVID-19 and associated social restrictions has radically transformed rider…
Data-Driven Prediction of Route-Level Energy Use for Mixed-Vehicle Transit Fleets
Afiya Ayman, Michael Wilbur, Amutheezan Sivagnanam +3
Due to increasing concerns about environmental impact, operating costs, and energy security, public transit agencies are seeking to reduce their fuel use by employing electric vehi…