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Hamid R. Rabiee
Sharif University of Technology
Machine learningPattern recognitionComputer visionMathematicsComputer science
216Publications
20H-index
1,705Citations
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Publications 220
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Autoencoders (AE) have recently been widely employed to approach the novelty detection problem. Trained only on the normal data, the AE is expected to reconstruct the normal data effectively while fail to regenerate the anomalous data, which could be utilized for novelty detection. However, in this paper, it is demonstrated that this does not always hold. AE often generalizes so perfectly that it can also reconstruct the anomalous data well. To address this problem, we propose a novel AE that ca...
#1Amir NajafiH-Index: 5
#1A. F. NajafiH-Index: 9
Last. Hamid R. RabieeH-Index: 20
view all 3 authors...
2 CitationsSource
#1Masroor Bayati (Sharif University of Technology)
#2Hamid R. Rabiee (Sharif University of Technology)H-Index: 20
Last. Hamid Alinejad-Rokny (UNSW: University of New South Wales)H-Index: 9
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Analysis of cancer mutational signatures have been instrumental in identification of responsible endogenous and exogenous molecular processes in cancer. The quantitative approach used to deconvolute mutational signatures is becoming an integral part of cancer research. Therefore, development of a stand-alone tool with a user-friendly interface for analysis of cancer mutational signatures is necessary. In this manuscript we introduce CANCERSIGN, which enables users to identify 3-mer and 5-mer mut...
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16 CitationsSource
#1Mahsa GhorbaniH-Index: 1
Last. Hamid R. Rabiee (Sharif University of Technology)H-Index: 20
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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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#1Maryam Ramezani (Sharif University of Technology)H-Index: 2
#2Mina Rafiei (Sharif University of Technology)
Last. Hamid R. Rabiee (Sharif University of Technology)H-Index: 20
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Source
#1Sina Sajadmanesh (Sharif University of Technology)H-Index: 1
#1Sina Sajadmanesh (Sharif University of Technology)H-Index: 3
Last. Hamid R. Rabiee (Sharif University of Technology)H-Index: 20
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Online social networks, World Wide Web, media, and technological networks, and other types of so-called information networks are ubiquitous nowadays. These information networks are inherently heterogeneous and dynamic. They are heterogeneous as they consist of multi-typed objects and relations, and they are dynamic as they are constantly evolving over time. One of the challenging issues in such heterogeneous and dynamic environments is to forecast those relationships in the network that will app...
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Jul 1, 2019 in ISIT (International Symposium on Information Theory)
#1Seyed Ali Osia (Sharif University of Technology)H-Index: 3
#2Borzoo Rassouli (University of Essex)H-Index: 9
Last. Deniz Gunduz (Imperial College London)H-Index: 33
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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 f-information adopted as the utility measure, and show that the optimal utility ...
1 CitationsSource
Jun 2, 2019 in NAACL (North American Chapter of the Association for Computational Linguistics)
#1Elham J. Barezi (HKU: University of Hong Kong)H-Index: 2
#2Ian Wood (National University of Ireland, Galway)H-Index: 4
Last. Hamid R. Rabiee (Sharif University of Technology)H-Index: 20
view all 4 authors...
Source
#1Seyed Ali OsiaH-Index: 3
#2Borzoo RassouliH-Index: 9
Last. Deniz GunduzH-Index: 33
view all 5 authors...
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...
1 Citations
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