activity
20182023
most citedRank and Rate: Multi-task Learning for Recommender Systems

40 citations · 72 across the 4 of their papers we have counts for

collaborators

5 papers

cs.IR2023★ 7 cited

Semi-supervised Adversarial Learning for Complementary Item Recommendation

Koby Bibas, Oren Sar Shalom, Dietmar Jannach

Complementary item recommendations are a ubiquitous feature of modern e-commerce sites. Such recommendations are highly effective when they are based on collaborative signals like…

cs.LG2020

A Black-Box Attack Model for Visually-Aware Recommender Systems

Rami Cohen, Oren Sar Shalom, Dietmar Jannach +1

Due to the advances in deep learning, visually-aware recommender systems (RS) have recently attracted increased research interest. Such systems combine collaborative signals with i…

cs.CL2018★ 23 cited

Understanding Convolutional Neural Networks for Text Classification

Alon Jacovi, Oren Sar Shalom, Yoav Goldberg

We present an analysis into the inner workings of Convolutional Neural Networks (CNNs) for processing text. CNNs used for computer vision can be interpreted by projecting filters i…

cs.IR2018★ 40 cited

Rank and Rate: Multi-task Learning for Recommender Systems

Guy Hadash, Oren Sar Shalom, Rita Osadchy

The two main tasks in the Recommender Systems domain are the ranking and rating prediction tasks. The rating prediction task aims at predicting to what extent a user would like any…

cs.IR2018★ 2 cited

Privacy and Fairness in Recommender Systems via Adversarial Training of User Representations

Yehezkel S. Resheff, Yanai Elazar, Moni Shahar +1

Latent factor models for recommender systems represent users and items as low dimensional vectors. Privacy risks of such systems have previously been studied mostly in the context…