The remarkable attention which fair clustering has received in the last ...
This workshop Report Out focuses on the foundational elements of trustwo...
As neural networks increasingly make critical decisions in high-stakes
s...
Single-shot auctions are commonly used as a means to sell goods, for exa...
Reinforcement Learning (RL) algorithms have been successfully applied to...
Consider a scenario where some upstream model developer must train a fai...
A recent approach to automated mechanism design, differentiable economic...
We propose a new architecture to approximately learn incentive compatibl...
Counterfactual explanations (CFEs) are an emerging technique under the
u...
Restless and collapsing bandits are commonly used to model constrained
r...
Facial recognition systems are increasingly deployed by private corporat...
Machine learning plays a role in many deployed decision systems, often i...
Despite the vulnerability of object detectors to adversarial attacks, ve...
Optimal auctions maximize a seller's expected revenue subject to individ...
We consider the problem faced by a recommender system which seeks to off...
Collaborative work often benefits from having teams or organizations wit...
Adversarial training, in which a network is trained on adversarial examp...
Standard adversarial attacks change the predicted class label of an imag...