We study the problem of in-context learning (ICL) with large language mo...
We present Project Florida, a system architecture and software developme...
With tools like GitHub Copilot, automatic code suggestion is no longer a...
Federated learning (FL) enables edge-devices to collaboratively learn a ...
In this paper we introduce "Federated Learning Utilities and Tools for
E...
We give simpler, sparser, and faster algorithms for differentially priva...
Building machine learning models from decentralized datasets located in
...
Deep learning frameworks leverage GPUs to perform massively-parallel
com...
We introduce an iterative optimization scheme for convex objectives
cons...
We examine a class of deep learning models with a tractable method to co...
In statistical learning for real-world large-scale data problems, one mu...
Restricted Boltzmann machines (RBMs) are energy-based neural-networks wh...
We consider the problem of reconstructing a signal from multi-layered
(p...
In this work, we consider compressed sensing reconstruction from M
measu...
Variational inference is a powerful concept that underlies many iterativ...