activity
20162020
most citedPartially Synthetic Data for Recommender Systems: Prediction Performance and Preference Hiding

7 citations · 16 across the 3 of their papers we have counts for

collaborators

7 papers

cs.IR20207 cited

Partially Synthetic Data for Recommender Systems: Prediction Performance and Preference Hiding

Manel Slokom, Martha Larson, Alan Hanjalic

This paper demonstrates the potential of statistical disclosure control for protecting the data used to train recommender systems. Specifically, we use a synthetic data generation…

cs.CV2020

Adversarial Color Enhancement: Generating Unrestricted Adversarial Images by Optimizing a Color Filter

Zhengyu Zhao, Zhuoran Liu, Martha Larson

We introduce an approach that enhances images using a color filter in order to create adversarial effects, which fool neural networks into misclassification. Our approach, Adversar…

cs.CV2019

Towards Large yet Imperceptible Adversarial Image Perturbations with Perceptual Color Distance

Zhengyu Zhao, Zhuoran Liu, Martha Larson

The success of image perturbations that are designed to fool image classifier is assessed in terms of both adversarial effect and visual imperceptibility. The conventional assumpti…

cs.MM2019

Remembering Winter Was Coming: Character-Oriented Video Summaries of TV Series

Xavier Bost, Serigne Gueye, Vincent Labatut +4

Today's popular TV series tend to develop continuous, complex plots spanning several seasons, but are often viewed in controlled and discontinuous conditions. Consequently, most vi…

cs.CV20195 cited

Who's Afraid of Adversarial Queries? The Impact of Image Modifications on Content-based Image Retrieval

Zhuoran Liu, Zhengyu Zhao, Martha Larson

An adversarial query is an image that has been modified to disrupt content-based image retrieval (CBIR) while appearing nearly untouched to the human eye. This paper presents an an…

cs.IR20184 cited

Factorization Machines for Data with Implicit Feedback

Babak Loni, Martha Larson, Alan Hanjalic

In this work, we propose FM-Pair, an adaptation of Factorization Machines with a pairwise loss function, making them effective for datasets with implicit feedback. The optimization…