Social media and social networking sites have become a global pinboard for exposition and
discussion of news, topics, and ideas, where social media users often update their opinions …

Predicting plausible links that may emerge between pairs of nodes is an important task in
social network analysis, with over a decade of active research. Here, we propose a novel …

The great success of modern machine learning models on large datasets is contingent on
extensive computational resources with high financial and environmental costs. One way to …

… Moreover, in contrast with the state of the art, our decoder is able to provide the spatial …
This work was done when Abir De was a post doctoral researcher at MPI-SWS, Germany. …

Spaced repetition is a technique for efficient memorization which uses repeated review of
content following a schedule determined by a spaced repetition algorithm to improve long-term …

Decisions are increasingly taken by both humans and machine learning models. However,
machine learning models are currently trained for full automation—they are not aware that …

Most supervised learning models are trained for full automation. However, their predictions
are sometimes worse than those by human experts on some specific instances. Motivated by …

Many social networks are characterized by actors (nodes) holding quantitative opinions
about movies, songs, sports, people, colleges, politicians, and so on. These opinions are …

In a wide variety of applications, humans interact with a complex environment by means of
asynchronous stochastic discrete events in continuous time. Can we design online …

Multiple lines of evidence suggest that predictive models may benefit from algorithmic triage.
Under algorithmic triage, a predictive model does not predict all instances but instead …