105 citations · 414 across the 31 of their papers we have counts for
32 papers
AMFPMC -- An improved method of detecting multiple types of drug-drug interactions using only known drug-drug interactions
Bar Vered, Guy Shtar, Lior Rokach +1
Adverse drug interactions are largely preventable causes of medical accidents, which frequently result in physician and emergency room encounters. The detection of drug interaction…
Transfer learning for time series classification using synthetic data generation
Yarden Rotem, Nathaniel Shimoni, Lior Rokach +1
In this paper, we propose an innovative Transfer learning for Time series classification method. Instead of using an existing dataset from the UCR archive as the source dataset, we…
Boosting Anomaly Detection Using Unsupervised Diverse Test-Time Augmentation
Seffi Cohen, Niv Goldshlager, Lior Rokach +1
Anomaly detection is a well-known task that involves the identification of abnormal events that occur relatively infrequently. Methods for improving anomaly detection performance h…
Evolving Context-Aware Recommender Systems With Users in Mind
Amit Livne, Eliad Shem Tov, Adir Solomon +3
A context-aware recommender system (CARS) applies sensing and analysis of user context to provide personalized services. The contextual information can be driven from sensors in or…
A framework for optimizing COVID-19 testing policy using a Multi Armed Bandit approach
Hagit Grushka-Cohen, Raphael Cohen, Bracha Shapira +2
Testing is an important part of tackling the COVID-19 pandemic. Availability of testing is a bottleneck due to constrained resources and effective prioritization of individuals is…
Iterative Boosting Deep Neural Networks for Predicting Click-Through Rate
Amit Livne, Roy Dor, Eyal Mazuz +3
The click-through rate (CTR) reflects the ratio of clicks on a specific item to its total number of views. It has significant impact on websites' advertising revenue. Learning soph…