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06/15/2023
ViP: A Differentially Private Foundation Model for Computer Vision
Artificial intelligence (AI) has seen a tremendous surge in capabilities...
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06/12/2023
"Private Prediction Strikes Back!” Private Kernelized Nearest Neighbors with Individual Renyi Filter
Most existing approaches of differentially private (DP) machine learning...
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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...
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05/06/2023
Bounding the Invertibility of Privacy-preserving Instance Encoding using Fisher Information
Privacy-preserving instance encoding aims to encode raw data as feature ...
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04/26/2023
Do SSL Models Have Déjà Vu? A Case of Unintended Memorization in Self-supervised Learning
Self-supervised learning (SSL) algorithms can produce useful image repre...
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04/05/2023
TM2D: Bimodality Driven 3D Dance Generation via Music-Text Integration
We propose a novel task for generating 3D dance movements that simultane...
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11/08/2022
The Interpolated MVU Mechanism For Communication-efficient Private Federated Learning
We consider private federated learning (FL), where a server aggregates d...
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10/24/2022
Analyzing Privacy Leakage in Machine Learning via Multiple Hypothesis Testing: A Lesson From Fano
Differential privacy (DP) is by far the most widely accepted framework f...
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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...
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09/21/2022
Measuring and Controlling Split Layer Privacy Leakage Using Fisher Information
Split learning and inference propose to run training/inference of a larg...
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09/12/2022
Cocktail Party Attack: Breaking Aggregation-Based Privacy in Federated Learning using Independent Component Analysis
Federated learning (FL) aims to perform privacy-preserving machine learn...
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07/04/2022
TM2T: Stochastic and Tokenized Modeling for the Reciprocal Generation of 3D Human Motions and Texts
Inspired by the strong ties between vision and language, the two intimat...
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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...
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03/25/2022
Origins of Low-dimensional Adversarial Perturbations
In this note, we initiate a rigorous study of the phenomenon of low-dime...
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03/15/2022
Privacy-Aware Compression for Federated Data Analysis
Federated data analytics is a framework for distributed data analysis wh...
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02/25/2022
Does Label Differential Privacy Prevent Label Inference Attacks?
Label differential privacy (LDP) is a popular framework for training pri...
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01/28/2022
Bounding Training Data Reconstruction in Private (Deep) Learning
Differential privacy is widely accepted as the de facto method for preve...
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01/04/2022
Submix: Practical Private Prediction for Large-Scale Language Models
Recent data-extraction attacks have exposed that language models can mem...
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12/23/2021
EIFFeL: Ensuring Integrity for Federated Learning
Federated learning (FL) enables clients to collaborate with a server to ...
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11/24/2021
ReAct: Out-of-distribution Detection With Rectified Activations
Out-of-distribution (OOD) detection has received much attention lately d...
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11/15/2021
On the Importance of Difficulty Calibration in Membership Inference Attacks
The vulnerability of machine learning models to membership inference att...
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11/12/2021
Action2video: Generating Videos of Human 3D Actions
We aim to tackle the interesting yet challenging problem of generating v...
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09/29/2021
BulletTrain: Accelerating Robust Neural Network Training via Boundary Example Mining
Neural network robustness has become a central topic in machine learning...
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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...
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08/15/2021
EventHPE: Event-based 3D Human Pose and Shape Estimation
Event camera is an emerging imaging sensor for capturing dynamics of mov...
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07/09/2021
Online Adaptation to Label Distribution Shift
Machine learning models often encounter distribution shifts when deploye...
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05/05/2021
Byzantine-Robust and Privacy-Preserving Framework for FedML
Federated learning has emerged as a popular paradigm for collaboratively...
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04/15/2021
Gradient-based Adversarial Attacks against Text Transformers
We propose the first general-purpose gradient-based attack against trans...
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03/22/2021
Fixes That Fail: Self-Defeating Improvements in Machine-Learning Systems
Machine-learning systems such as self-driving cars or virtual assistants...
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02/23/2021
Measuring Data Leakage in Machine-Learning Models with Fisher Information
Machine-learning models contain information about the data they were tra...
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02/09/2021
Making Paper Reviewing Robust to Bid Manipulation Attacks
Most computer science conferences rely on paper bidding to assign review...
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07/30/2020
Action2Motion: Conditioned Generation of 3D Human Motions
Action recognition is a relatively established task, where givenan input...
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02/24/2020
TrojanNet: Embedding Hidden Trojan Horse Models in Neural Networks
The complexity of large-scale neural networks can lead to poor understan...
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01/09/2020
Secure multiparty computations in floating-point arithmetic
Secure multiparty computations enable the distribution of so-called shar...
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11/08/2019
Certified Data Removal from Machine Learning Models
Good data stewardship requires removal of data at the request of the dat...
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10/16/2019
A New Defense Against Adversarial Images: Turning a Weakness into a Strength
Natural images are virtually surrounded by low-density misclassified reg...
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05/17/2019
Simple Black-box Adversarial Attacks
We propose an intriguingly simple method for the construction of adversa...
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04/16/2019
AT-GAN: A Generative Attack Model for Adversarial Transferring on Generative Adversarial Nets
Recent studies have discovered the vulnerability of Deep Neural Networks...
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03/05/2019
Exploiting Emotions for Fake News Detection on Social Media
Microblog has become a popular platform for people to post, share, and s...
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09/24/2018
Low Frequency Adversarial Perturbation
Recently, machine learning security has received significant attention. ...
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06/19/2018
An empirical study on evaluation metrics of generative adversarial networks
Evaluating generative adversarial networks (GANs) is inherently challeng...
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10/31/2017