The surveillance of a pandemic is a challenging task, especially when cr...
Irregularities in public health data streams (like COVID-19 Cases) hampe...
Large-scale administrative or observational datasets are increasingly us...
We provide practical, efficient, and nonparametric methods for auditing ...
We present a methodology for formulating simplifying abstractions in mac...
We consider the task of evaluating policies of algorithmic resource
allo...
There is significant interest in learning and optimizing a complex syste...
The COVID-19 pandemic provides new motivation for a classic problem in
e...
Each year, there are nearly 4 million youth experiencing homelessness (Y...
Solving optimization problems with unknown parameters often requires lea...
Persistence diagrams, a key tool in the field of Topological Data Analys...
A rising vision for AI in the open world centers on the development of
s...
Machine learning components commonly appear in larger decision-making
pi...
Real-world applications often combine learning and optimization problems...
Integrating logical reasoning within deep learning architectures has bee...
Influence maximization is a widely used model for information disseminat...
Stackelberg security games are a critical tool for maximizing the utilit...
Digital Adherence Technologies (DATs) are an increasingly popular method...
The integrity of democratic elections depends on voters' access to accur...
Creating impact in real-world settings requires artificial intelligence
...
Social and behavioral interventions are a critical tool for governments ...
Submodular functions have applications throughout machine learning, but ...
Election control considers the problem of an adversary who attempts to t...
We define a class of zero-sum games with combinatorial structure, where ...
While reigning models of diffusion have privileged the structure of a gi...