research
∙
09/21/2023
Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation
We study the problem of in-context learning (ICL) with large language mo...
share
research
∙
07/21/2023
Project Florida: Federated Learning Made Easy
We present Project Florida, a system architecture and software developme...
research
∙
01/06/2023
TrojanPuzzle: Covertly Poisoning Code-Suggestion Models
With tools like GitHub Copilot, automatic code suggestion is no longer a...
research
∙
04/27/2022
Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning
Federated learning (FL) enables edge-devices to collaboratively learn a ...
research
∙
03/25/2022
FLUTE: A Scalable, Extensible Framework for High-Performance Federated Learning Simulations
In this paper we introduce "Federated Learning Utilities and Tools for E...
research
∙
10/13/2021
Differentially Private Fine-tuning of Language Models
We give simpler, sparser, and faster algorithms for differentially priva...
research
∙
06/16/2020
Federated Survival Analysis with Discrete-Time Cox Models
Building machine learning models from decentralized datasets located in ...
research
∙
12/12/2019
Efficient Per-Example Gradient Computations in Convolutional Neural Networks
Deep learning frameworks leverage GPUs to perform massively-parallel com...
research
∙
09/17/2018
Approximate message-passing for convex optimization with non-separable penalties
We introduce an iterative optimization scheme for convex objectives cons...
research
∙
05/24/2018
Entropy and mutual information in models of deep neural networks
We examine a class of deep learning models with a tractable method to co...
research
∙
06/02/2017
Streaming Bayesian inference: theoretical limits and mini-batch approximate message-passing
In statistical learning for real-world large-scale data problems, one mu...
research
∙
02/10/2017
A Deterministic and Generalized Framework for Unsupervised Learning with Restricted Boltzmann Machines
Restricted Boltzmann machines (RBMs) are energy-based neural-networks wh...
research
∙
01/24/2017
Multi-Layer Generalized Linear Estimation
We consider the problem of reconstructing a signal from multi-layered (p...
research
∙
06/13/2016
Inferring Sparsity: Compressed Sensing using Generalized Restricted Boltzmann Machines
In this work, we consider compressed sensing reconstruction from M measu...
research
∙
09/22/2014
