Membership inference attacks are designed to determine, using black box
...
Learning generalizeable policies from visual input in the presence of vi...
Federated learning is an increasingly popular paradigm that enables a la...
Machine learning models are updated as new data is acquired or new
archi...
Federated learning is an increasingly popular paradigm that enables a la...
In this work we formulate and formally characterize group fairness as a
...
Agents trained via deep reinforcement learning (RL) routinely fail to
ge...
Common fairness definitions in machine learning focus on balancing notio...
Extracting the instantaneous heart rate (iHR) from face videos has been ...
It is becoming increasingly clear that users should own and control thei...