no code implementations • 19 Feb 2018 • Ali Zarezade, Abir De, Utkarsh Upadhyay, Hamid R. Rabiee, Manuel Gomez-Rodriguez
At a network level, they may increase activity by incentivizing a few influential users to take more actions, which in turn will trigger additional actions by other users.
no code implementations • 5 Oct 2017 • Amir Najafi, Abolfazl Motahari, Hamid R. Rabiee
A Bernoulli Mixture Model (BMM) is a finite mixture of random binary vectors with independent dimensions.
no code implementations • 21 Jun 2017 • Sina Sajadmanesh, Jiawei Zhang, Hamid R. Rabiee
In this paper, we try to solve the problem of temporal link prediction in information networks.
no code implementations • 26 Oct 2016 • Sina Sajadmanesh, Sina Jafarzadeh, Seyed Ali Osia, Hamid R. Rabiee, Hamed Haddadi, Yelena Mejova, Mirco Musolesi, Emiliano De Cristofaro, Gianluca Stringhini
In this paper, we present a large-scale study of recipes published on the web and their content, aiming to understand cuisines and culinary habits around the world.
no code implementations • 23 Nov 2016 • Ali Zarezade, Sina Jafarzadeh, Hamid R. Rabiee
People share the exact location and time of their check-ins and are influenced by their friends.
no code implementations • 7 Feb 2017 • Ali Khodadadi, Seyed Abbas Hosseini, Erfan Tavakoli, Hamid R. Rabiee
However, typical point process based models often considered the impact of peer influence and content on the user participation and neglected other factors.
no code implementations • 2 Oct 2016 • Seyed Abbas Hosseini, Ali Khodadadi, Soheil Arabzade, Hamid R. Rabiee
These capabilities allow the proposed model to adapt its temporal and topical complexity according to the complexity of data, which makes it a suitable candidate for real world scenarios.
no code implementations • 24 Feb 2016 • Alireza Ghasemi, Hamid R. Rabiee, Mohammad T. Manzuri, M. H. Rohban
The proposed approach uses a Bayesian framework to precisely compute the class boundary and therefore can utilize domain information in form of prior knowledge in the framework.
no code implementations • 24 Nov 2013 • Amirreza Shaban, Hamid R. Rabiee, Mahyar Najibi
Data coding as a building block of several image processing algorithms has been received great attention recently.
no code implementations • 5 Feb 2014 • Ali Zarezade, Hamid R. Rabiee, Ali Soltani-Farani, Ahmad Khajenezhad
Since the target's appearance often changes slowly in a video sequence, it is assumed that the target in the current frame and the best candidates of a small number of previous frames, belong to a common subspace.
no code implementations • 6 Aug 2013 • Ali Soltani-Farani, Hamid R. Rabiee, Seyyed Abbas Hosseini
This paper presents a structured dictionary-based model for hyperspectral data that incorporates both spectral and contextual characteristics of a spectral sample, with the goal of hyperspectral image classification.
no code implementations • 18 Oct 2018 • Amir Najafi, Saeed Ilchi, Amir H. Saberi, Seyed Abolfazl Motahari, Babak H. Khalaj, Hamid R. Rabiee
We study the sample complexity of learning a high-dimensional simplex from a set of points uniformly sampled from its interior.
no code implementations • 21 Nov 2018 • Ehsan Montahaei, Mahsa Ghorbani, Mahdieh Soleymani Baghshah, Hamid R. Rabiee
However, this approach has not been extensively utilized for classifier training.
no code implementations • CVPR 2013 • Amirreza Shaban, Hamid R. Rabiee, Mehrdad Farajtabar, Marjan Ghazvininejad
Exploiting the local similarity of a descriptor and its nearby bases, a global measure of association of a descriptor to all the bases is computed.
no code implementations • CVPR 2016 • Sarah Rastegar, Mahdieh Soleymani, Hamid R. Rabiee, Seyed Mohsen Shojaee
In this paper, we propose a multimodal deep learning framework (MDL-CW) that exploits the cross weights between representation of modalities, and try to gradually learn interactions of the modalities in a deep network manner (from low to high level interactions).
no code implementations • NAACL 2019 • Elham J. Barezi, Ian D. Wood, Pascale Fung, Hamid R. Rabiee
We can then solve efficiently the problem of multi-label learning with an intractably large number of interdependent labels, such as automatic tagging of Wikipedia pages.
no code implementations • 15 Sep 2019 • Ali Khodadadi, Seyed Abbas Hosseini, Ehsan Pajouheshgar, Farnam Mansouri, Hamid R. Rabiee
In this approach which is more realistic in real world online services, at each time-step the model predicts the user return time instead of predicting a churn label.
no code implementations • 23 Nov 2020 • Rassa Ghavami Modegh, Mehrab Hamidi, Saeed Masoudian, Amir Mohseni, Hamzeh Lotfalinezhad, Mohammad Ali Kazemi, Behnaz Moradi, Mahyar Ghafoori, Omid Motamedi, Omid Pournik, Kiara Rezaei-Kalantari, Amirreza Manteghinezhad, Shaghayegh Haghjooy Javanmard, Fateme Abdoli Nezhad, Ahmad Enhesari, Mohammad Saeed Kheyrkhah, Razieh Eghtesadi, Javid Azadbakht, Akbar Aliasgharzadeh, Mohammad Reza Sharif, Ali Khaleghi, Abbas Foroutan, Hossein Ghanaati, Hamed Dashti, Hamid R. Rabiee
We designed a new interpretable deep neural network to distinguish healthy people, patients with COVID-19, and patients with other pneumonia diseases from axial lung CT-scan images.
no code implementations • 31 Dec 2020 • Faezeh Faez, Yassaman Ommi, Mahdieh Soleymani Baghshah, Hamid R. Rabiee
Deep generative models have achieved great success in areas such as image, speech, and natural language processing in the past few years.
no code implementations • 18 Mar 2021 • Reza Shirkavand, Sana Ayromlou, Soroush Farghadani, Maedeh-sadat Tahaei, Fattane Pourakpour, Bahareh Siahlou, Zeynab Khodakarami, Mohammad H. Rohban, Mansoor Fatehi, Hamid R. Rabiee
Fazekas scale facilitates an accurate quantitative assessment of the severity of white matter lesions and hence the disease.
no code implementations • 15 Apr 2021 • Nasrin Taghizadeh, Ehsan Doostmohammadi, Elham Seifossadat, Hamid R. Rabiee, Maedeh S. Tahaei
We have released Sina-BERT, a language model pre-trained on BERT (Devlin et al., 2018) to address the lack of a high-quality Persian language model in the medical domain.
no code implementations • 22 May 2021 • Mohammadreza Doostmohammadian, Themistoklis Charalambous, Miadreza Shafie-khah, Hamid R. Rabiee, Usman A. Khan
Observability and estimation are closely tied to the system structure, which can be visualized as a system graph--a graph that captures the inter-dependencies within the state variables.
no code implementations • 20 Sep 2021 • Mohammadreza Doostmohammadian, Houman Zarrabi, Hamid R. Rabiee, Usman A. Khan, Themistoklis Charalambous
First, for performance analysis in the attack-free case, we show that the proposed distributed estimation is unbiased with bounded mean-square deviation in steady-state.
no code implementations • 7 Oct 2021 • Yassaman Ommi, Matin Yousefabadi, Faezeh Faez, Amirmojtaba Sabour, Mahdieh Soleymani Baghshah, Hamid R. Rabiee
With an increase in the number of applications where data is represented as graphs, the problem of graph generation has recently become a hot topic.
no code implementations • 29 Sep 2021 • Seyyede Fatemeh Seyyedsalehi, Mahdieh Soleymani Baghshah, Hamid R. Rabiee
Because of the complex relationship between the computational path of output variables in structured models, a feature can affect the value of output through other ones.
no code implementations • 2 Dec 2021 • Faeze Ghorbanpour, Maryam Ramezani, Mohammad A. Fazli, Hamid R. Rabiee
The availability and interactive nature of social media have made them the primary source of news around the globe.
no code implementations • 27 Jan 2022 • Rassa Ghavami Modegh, Ahmad Salimi, Alireza Dizaji, Hamid R. Rabiee
Despite the state-of-the-art performance of deep convolutional neural networks, they are susceptible to bias and malfunction in unseen situations.
no code implementations • 20 Feb 2022 • S. Fatemeh Seyyedsalehi, Mahdieh Soleymani, Hamid R. Rabiee
Because of the complex relationship between the computational path of output variables in structured models, a feature can affect the value of output through other ones.
no code implementations • 15 Sep 2022 • Gholamali Aminian, Armin Behnamnia, Roberto Vega, Laura Toni, Chengchun Shi, Hamid R. Rabiee, Omar Rivasplata, Miguel R. D. Rodrigues
We propose learning methods for problems where feedback is missing for some samples, so there are samples with feedback and samples missing-feedback in the logged data.
no code implementations • 20 Sep 2022 • Faezeh Faez, Negin Hashemi Dijujin, Mahdieh Soleymani Baghshah, Hamid R. Rabiee
Deep learning-based graph generation approaches have remarkable capacities for graph data modeling, allowing them to solve a wide range of real-world problems.
no code implementations • 4 Dec 2022 • Gita Sarafraz, Armin Behnamnia, Mehran Hosseinzadeh, Ali Balapour, Amin Meghrazi, Hamid R. Rabiee
This paper provides the first systematic review of DG and DA on functional brain signals to fill the gap of the absence of a comprehensive study in this era.
1 code implementation • Social Network Analysis and Mining 2023 • Faeze Ghorbanpour, Maryam Ramezani, Mohammad Amin Fazli, Hamid R. Rabiee
In this paper, we propose a novel and efficient similarity and transformer-based detection algorithm called Fake News Revealer (FNR), which uses text and images of news to detect fake news.
no code implementations • 25 Jul 2023 • Mohammmadmahdi Maheri, Reza Abdollahzadeh, Bardia Mohammadi, Mina Rafiei, Jafar Habibi, Hamid R. Rabiee
In practical scenarios, the effectiveness of sequential recommendation systems is hindered by the user cold-start problem, which arises due to limited interactions for accurately determining user preferences.
no code implementations • 7 Oct 2023 • S. M. F. Sani, Seyed Abbas Hosseini, Hamid R. Rabiee
Recent studies have attempted to mitigate this bias by collecting small amounts of unbiased data.
no code implementations • 27 Oct 2023 • Mohammadreza Doostmohammadian, Alireza Aghasi, Maria Vrakopoulou, Hamid R. Rabiee, Usman A. Khan, Themistoklis Charalambou
This paper proposes two nonlinear dynamics to solve constrained distributed optimization problem for resource allocation over a multi-agent network.
no code implementations • 5 Mar 2024 • Mohammad Rostami, Amin Ghariyazi, Hamed Dashti, Mohammad Hossein Rohban, Hamid R. Rabiee
This is because most existing methods are trained on separate datasets with different genes and cells, which limits their generalizability.
no code implementations • 13 May 2024 • Karim Abbasi, Parvin Razzaghi, Amin Ghareyazi, Hamid R. Rabiee
This paper aims to integrate retrieved similar hard protein-ligand pairs in PLA prediction (i. e., task prediction step) using a semi-supervised graph convolutional network (GCN).
1 code implementation • 8 Jun 2019 • Maryam Ramezani, Mina Rafiei, Soroush Omranpour, Hamid R. Rabiee
Therefore, one of the challenging tasks in this area is to identify fake and real news in early stages of propagation.
1 code implementation • 23 Jan 2018 • Maryam Ramezani, Ali Khodadadi, Hamid R. Rabiee
Community detection in social networks has become a popular topic of research during the last decade.
1 code implementation • 8 Apr 2021 • Mahsa Ghorbani, Mojtaba Bahrami, Anees Kazi, Mahdieh SoleymaniBaghshah, Hamid R. Rabiee, Nassir Navab
The soft pseudo-labels are then used to train a deep student network for disease prediction of unseen test data for which the graph modality is unavailable.
1 code implementation • 14 Jun 2016 • Maryam Tahani, Ali M. A. Hemmatyar, Hamid R. Rabiee, Maryam Ramezani
In this article, we investigate the diffusion network extraction (DNE) problem when the underlying network is dynamic and latent.
1 code implementation • 24 Feb 2016 • Alireza Ghasemi, Hamid R. Rabiee, Mohsen Fadaee, Mohammad T. Manzuri, Mohammad H. Rohban
Such problems arise in many real-world situations and are known as the problem of learning from positive and unlabeled data.
1 code implementation • 2 Oct 2023 • Maryam Ramezani, Aryan Ahadinia, Erfan Farhadi, Hamid R. Rabiee
In this paper, we propose a novel method called DANI to infer the underlying network while preserving its structural properties.
1 code implementation • 8 Mar 2017 • Seyed Ali Osia, Ali Shahin Shamsabadi, Sina Sajadmanesh, Ali Taheri, Kleomenis Katevas, Hamid R. Rabiee, Nicholas D. Lane, Hamed Haddadi
To this end, instead of performing the whole operation on the cloud, we let an IoT device to run the initial layers of the neural network, and then send the output to the cloud to feed the remaining layers and produce the final result.
1 code implementation • 4 Oct 2017 • Seyed Ali Osia, Ali Shahin Shamsabadi, Ali Taheri, Kleomenis Katevas, Hamid R. Rabiee, Nicholas D. Lane, Hamed Haddadi
Our evaluations show that by using certain kind of fine-tuning and embedding techniques and at a small processing costs, we can greatly reduce the level of information available to unintended tasks applied to the data feature on the cloud, and hence achieving the desired tradeoff between privacy and performance.
1 code implementation • IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2016 • Sina Sajadmanesh, Hamid R. Rabiee, Ali Khodadadi
Once a user (called source user) of a social network (called source network) joins a new social network (called target network), a new inter-network link (called anchor link) is formed between the source and target networks.
Social and Information Networks Physics and Society
1 code implementation • 3 Oct 2020 • Maryam Ramezani, Aryan Ahadinia, Amirmohammad Ziaei, Hamid R. Rabiee
Therefore, the problem of missing data is a crucial and unavoidable issue in the analysis and modeling of real-world social networks.
1 code implementation • 29 Aug 2020 • Mohammadreza Salehi, Ainaz Eftekhar, Niousha Sadjadi, Mohammad Hossein Rohban, Hamid R. Rabiee
Puzzle-solving, as a pretext task of self-supervised learning (SSL) methods, has earlier proved its ability in learning semantically meaningful features.
1 code implementation • 9 Feb 2018 • Seyed Ali Osia, Ali Taheri, Ali Shahin Shamsabadi, Kleomenis Katevas, Hamed Haddadi, Hamid R. Rabiee
We present and evaluate Deep Private-Feature Extractor (DPFE), a deep model which is trained and evaluated based on information theoretic constraints.
1 code implementation • 4 Mar 2017 • Seyed Abbas Hosseini, Keivan Alizadeh, Ali Khodadadi, Ali Arabzadeh, Mehrdad Farajtabar, Hongyuan Zha, Hamid R. Rabiee
Poisson factorization is a probabilistic model of users and items for recommendation systems, where the so-called implicit consumer data is modeled by a factorized Poisson distribution.
1 code implementation • 30 Sep 2017 • Sina Sajadmanesh, Sogol Bazargani, Jiawei Zhang, Hamid R. Rabiee
In this paper, we try to solve the problem of continuous-time relationship prediction in dynamic and heterogeneous information networks.
1 code implementation • 27 Feb 2021 • Mahsa Ghorbani, Anees Kazi, Mahdieh Soleymani Baghshah, Hamid R. Rabiee, Nassir Navab
This is accomplished by associating a graph-based neural network to each class, which is responsible for weighting the class samples and changing the importance of each sample for the classifier.
1 code implementation • 12 Mar 2020 • Mohammadreza Salehi, Atrin Arya, Barbod Pajoum, Mohammad Otoofi, Amirreza Shaeiri, Mohammad Hossein Rohban, Hamid R. Rabiee
To address this problem, we propose a novel AE that can learn more semantically meaningful features.
1 code implementation • 21 Nov 2018 • Mahsa Ghorbani, Mahdieh Soleymani Baghshah, Hamid R. Rabiee
The goal of graph embedding is to find a low dimensional representation of graph nodes that preserves the graph information.
3 code implementations • CVPR 2021 • Mohammadreza Salehi, Niousha Sadjadi, Soroosh Baselizadeh, Mohammad Hossein Rohban, Hamid R. Rabiee
Unsupervised representation learning has proved to be a critical component of anomaly detection/localization in images.