In recommendation settings, there is an apparent trade-off between the g...
Recommendation systems rely on user-provided data to learn about item qu...
There has been a steep recent increase in the number of large language m...
In this white paper, we synthesize key points made during presentations ...
Many recommender systems are based on optimizing a linear weighting of
d...
Healthcare data in the United States often records only a patient's coar...
User-solicited ratings systems in online marketplaces suffer from a
cold...
Digital recommender systems such as Spotify and Netflix affect not only
...
Algorithms provide powerful tools for detecting and dissecting human bia...
Modern city governance relies heavily on crowdsourcing (or "co-productio...
This study proposes voltage-dependent-synaptic plasticity (VDSP), a nove...
Ranking, recommendation, and retrieval systems are widely used in online...
Alzheimers disease is a fatal progressive brain disorder that worsens wi...
Strategic classification studies the design of a classifier robust to th...
Due to the Covid-19 pandemic, more than 500 US-based colleges and
univer...
Every representative democracy must specify a mechanism under which vote...
Recommender systems – and especially matrix factorization-based
collabor...
This work proposes a hybrid Brain Computer Interface system for the
auto...
The University of California recently suspended through 2024 the require...
Public and private institutions must often allocate scare resources unde...
Elections and opinion polls often have many candidates, with the aim to
...
Uber and Lyft ride-hailing marketplaces use dynamic pricing, often calle...
We provide an NLP framework to uncover four linguistic dimensions of
pol...
Platforms critically rely on rating systems to learn the quality of mark...
A public decision-making problem consists of a set of issues, each with
...
Modern online platforms rely on effective rating systems to learn about
...
Word embeddings use vectors to represent words such that the geometry be...
Many societal decision problems lie in high-dimensional continuous space...
We propose a Bayesian model of unsupervised semantic role induction in
m...