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Hamid R. Rabiee
Sharif University of Technology
199Publications
17H-index
1,253Citations
Publications 199
Newest
Published on Sep 15, 2019in arXiv: Learning
Ali Khodadadi4
Estimated H-index: 4
,
Seyed Abbas Hosseini + 2 AuthorsHamid R. Rabiee17
Estimated H-index: 17
User churn is an important issue in online services that threatens the health and profitability of services. Most of the previous works on churn prediction convert the problem into a binary classification task where the users are labeled as churned and non-churned. More recently, some works have tried to convert the user churn prediction problem into the prediction of user return time. In this approach which is more realistic in real world online services, at each time-step the model predicts th...
Sina Sajadmanesh2
Estimated H-index: 2
(Sharif University of Technology),
Sogol Bazargani (Sharif University of Technology)+ 1 AuthorsHamid R. Rabiee17
Estimated H-index: 17
(Sharif University of Technology)
Seyed Ali Ossia1
Estimated H-index: 1
(Sharif University of Technology),
Borzoo Rassouli6
Estimated H-index: 6
(University of Essex)
+ 2 AuthorsDeniz Gunduz32
Estimated H-index: 32
(Imperial College London)
Published on Jun 2, 2019 in NAACL (North American Chapter of the Association for Computational Linguistics)
Elham J. Barezi1
Estimated H-index: 1
(Sharif University of Technology),
Ian wood1
Estimated H-index: 1
+ 1 AuthorsHamid R. Rabiee17
Estimated H-index: 17
(Sharif University of Technology)
Published on Jan 1, 2019in arXiv: Information Theory
Seyed Ali Ossia1
Estimated H-index: 1
,
Borzoo Rassouli6
Estimated H-index: 6
+ 2 AuthorsDeniz Gunduz32
Estimated H-index: 32
Privacy-preserving data release is about disclosing information about useful data while retaining the privacy of sensitive data. Assuming that the sensitive data is threatened by a brute-force adversary, we define Guessing Leakage as a measure of privacy, based on the concept of guessing. After investigating the properties of this measure, we derive the optimal utility-privacy trade-off via a linear program with any finformation adopted as the utility measure, and show that the optimal utilit...
Published on Jun 10, 2019in arXiv: Social and Information Networks
Maryam Ramezani2
Estimated H-index: 2
(Sharif University of Technology),
Mina Rafiei (Sharif University of Technology)+ 1 AuthorsHamid R. Rabiee17
Estimated H-index: 17
(Sharif University of Technology)
Making disguise between real and fake news propagation through online social networks is an important issue in many applications. The time gap between the news release time and detection of its label is a significant step towards broadcasting the real information and avoiding the fake. Therefore, one of the challenging tasks in this area is to identify fake and real news in early stages of propagation. However, there is a trade-off between minimizing the time gap and maximizing accuracy. Despite...
Published on 2019in IEEE Systems Journal4.46
Mohammadreza Doostmohammadian5
Estimated H-index: 5
,
Hamid R. Rabiee17
Estimated H-index: 17
,
Usman A. Khan17
Estimated H-index: 17
Zeinab Golgooni (Sharif University of Technology), Sara Mirsadeghi1
Estimated H-index: 1
(Royan Institute)
+ 4 AuthorsHamid R. Rabiee17
Estimated H-index: 17
(Sharif University of Technology)
An early characterization of drug-induced cardiotoxicity may be possible by combining comprehensive in vitro proarrhythmia assay and deep learning techniques. We aimed to develop a method to automatically detect irregular beating rhythm of field potentials recorded from human pluripotent stem cells (hPSC) derived cardiomyocytes (hPSC-CM) by multi-electrode array (MEA) system. We included field potentials from 380 experiments, which were labeled as normal or arrhythmic by electrophysiology expert...
Published on Dec 1, 2018in Social Network Analysis and Mining
Hamidreza Mahyar5
Estimated H-index: 5
(Sharif University of Technology),
Rouzbeh Hasheminezhad2
Estimated H-index: 2
(ETH Zurich)
+ 4 AuthorsHamid R. Rabiee17
Estimated H-index: 17
(Sharif University of Technology)
This paper addresses the problem of identifying central nodes from the information flow standpoint in a social network. Betweenness centrality is the most prominent measure that shows the node importance from the information flow standpoint in the network. High betweenness centrality nodes play crucial roles in the spread of propaganda, ideologies, or gossips in social networks, the bottlenecks in communication networks, and the connector hubs in biological systems. In this paper, we introduce D...
Published on 2019in arXiv: Learning
Mahsa Ghorbani1
Estimated H-index: 1
,
Mahdieh Soleymani Baghshah9
Estimated H-index: 9
,
Hamid R. Rabiee17
Estimated H-index: 17
(Sharif University of Technology)
Graph embedding is an important approach for graph analysis tasks such as node classification and link prediction. The goal of graph embedding is to find a low dimensional representation of graph nodes that preserves the graph information. Recent methods like Graph Convolutional Network (GCN) try to consider node attributes (if available) besides node relations and learn node embeddings for unsupervised and semi-supervised tasks on graphs. On the other hand, multi-layer graph analysis has been r...
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