research
∙
04/23/2021
Unsupervised Information Obfuscation for Split Inference of Neural Networks
Splitting network computations between the edge device and a server enab...
share
research
∙
04/18/2021
Federated Learning of User Verification Models Without Sharing Embeddings
We consider the problem of training User Verification (UV) models in fed...
research
∙
07/09/2020
Federated Learning of User Authentication Models
Machine learning-based User Authentication (UA) models have been widely ...
research
∙
07/28/2019
Are Odds Really Odd? Bypassing Statistical Detection of Adversarial Examples
Deep learning classifiers are known to be vulnerable to adversarial exam...
research
∙
05/01/2019
Dropping Pixels for Adversarial Robustness
Deep neural networks are vulnerable against adversarial examples. In thi...
research
∙
03/21/2018
Assessing Shape Bias Property of Convolutional Neural Networks
It is known that humans display "shape bias" when classifying new items,...
research
∙
03/16/2018
Semantic Adversarial Examples
Deep neural networks are known to be vulnerable to adversarial examples,...
research
∙
08/14/2017
Attacking Automatic Video Analysis Algorithms: A Case Study of Google Cloud Video Intelligence API
Due to the growth of video data on Internet, automatic video analysis ha...
research
∙
03/26/2017
Deceiving Google's Cloud Video Intelligence API Built for Summarizing Videos
Despite the rapid progress of the techniques for image classification, v...
research
∙
03/20/2017
On the Limitation of Convolutional Neural Networks in Recognizing Negative Images
Convolutional Neural Networks (CNNs) have achieved state-of-the-art perf...
research
∙
08/27/2016
Learning Temporal Dependence from Time-Series Data with Latent Variables
We consider the setting where a collection of time series, modeled as ra...
research
∙
07/10/2014
Real-Time Impulse Noise Suppression from Images Using an Efficient Weighted-Average Filtering
In this paper, we propose a method for real-time high density impulse no...
research
∙
01/23/2014
