research
∙
06/15/2023
ViP: A Differentially Private Foundation Model for Computer Vision
Artificial intelligence (AI) has seen a tremendous surge in capabilities...
share
research
∙
06/05/2023
Information Flow Control in Machine Learning through Modular Model Architecture
In today's machine learning (ML) models, any part of the training data c...
research
∙
10/19/2022
Learning to Invert: Simple Adaptive Attacks for Gradient Inversion in Federated Learning
Gradient inversion attack enables recovery of training samples from mode...
research
∙
05/15/2022
Promoting Saliency From Depth: Deep Unsupervised RGB-D Saliency Detection
Growing interests in RGB-D salient object detection (RGB-D SOD) have bee...
research
∙
03/25/2022
Origins of Low-dimensional Adversarial Perturbations
In this note, we initiate a rigorous study of the phenomenon of low-dime...
research
∙
02/25/2022
Does Label Differential Privacy Prevent Label Inference Attacks?
Label differential privacy (LDP) is a popular framework for training pri...
research
∙
12/23/2021
EIFFeL: Ensuring Integrity for Federated Learning
Federated learning (FL) enables clients to collaborate with a server to ...
research
∙
08/15/2021
Human Pose and Shape Estimation from Single Polarization Images
This paper focuses on a new problem of estimating human pose and shape f...
research
∙
03/22/2021
Fixes That Fail: Self-Defeating Improvements in Machine-Learning Systems
Machine-learning systems such as self-driving cars or virtual assistants...
research
∙
07/30/2020
Action2Motion: Conditioned Generation of 3D Human Motions
Action recognition is a relatively established task, where givenan input...
research
∙
04/16/2019
