Search Results for author: Hamid R. Rabiee

Found 54 papers, 19 papers with code

CRISPR: Ensemble Model

no code implementations5 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.

Ensemble Learning Specificity

DANI: Fast Diffusion Aware Network Inference with Preserving Topological Structure Property

1 code implementation2 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.

Time Series

ClusterSeq: Enhancing Sequential Recommender Systems with Clustering based Meta-Learning

no code implementations25 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.

Clustering Meta-Learning +1

FNR: a similarity and transformer-based approach to detect multi-modal fake news in social media

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.

Fake News Detection

Domain Adaptation and Generalization on Functional Medical Images: A Systematic Survey

no code implementations4 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.

Domain Generalization

SCGG: A Deep Structure-Conditioned Graph Generative Model

no code implementations20 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.

Graph Generation Graph Representation Learning

Semi-supervised Batch Learning From Logged Data

no code implementations15 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.

counterfactual

SOInter: A Novel Deep Energy Based Interpretation Method for Explaining Structured Output Models

no code implementations20 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.

LAP: An Attention-Based Module for Concept Based Self-Interpretation and Knowledge Injection in Convolutional Neural Networks

no code implementations27 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.

Decision Making valid

FNR: A Similarity and Transformer-Based Approachto Detect Multi-Modal FakeNews in Social Media

no code implementations2 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.

CCGG: A Deep Autoregressive Model for Class-Conditional Graph Generation

no code implementations7 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.

Graph Generation

SOInter: A Novel Deep Energy-Based Interpretation Method for Explaining Structured Output Models

no code implementations29 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.

Distributed Detection and Mitigation of Biasing Attacks over Multi-Agent Networks

no code implementations20 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.

Analysis of Contractions in System Graphs: Application to State Estimation

no code implementations22 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.

Clustering

SINA-BERT: A pre-trained Language Model for Analysis of Medical Texts in Persian

no code implementations15 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.

Language Modelling Retrieval +1

GKD: Semi-supervised Graph Knowledge Distillation for Graph-Independent Inference

1 code implementation8 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.

Disease Prediction graph construction +1

RA-GCN: Graph Convolutional Network for Disease Prediction Problems with Imbalanced Data

1 code implementation27 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.

Disease Prediction Node Classification

Deep Graph Generators: A Survey

no code implementations31 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.

Graph Generation Graph Representation Learning

Puzzle-AE: Novelty Detection in Images through Solving Puzzles

1 code implementation29 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.

Anomaly Detection Novelty Detection +2

ChOracle: A Unified Statistical Framework for Churn Prediction

no code implementations15 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.

Binary Classification Point Processes

News Labeling as Early as Possible: Real or Fake?

1 code implementation8 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.

A Submodular Feature-Aware Framework for Label Subset Selection in Extreme Classification Problems

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.

General Classification Multi-Label Learning

On Statistical Learning of Simplices: Unmixing Problem Revisited

no code implementations18 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.

Steering Social Activity: A Stochastic Optimal Control Point Of View

no code implementations19 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.

Point Processes

Deep Private-Feature Extraction

1 code implementation9 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.

Community detection using diffusion information

1 code implementation23 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.

Community Detection

Reliable Clustering of Bernoulli Mixture Models

no code implementations5 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.

Clustering

Privacy-Preserving Deep Inference for Rich User Data on The Cloud

1 code implementation4 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.

Privacy Preserving

Continuous-Time Relationship Prediction in Dynamic Heterogeneous Information Networks

1 code implementation30 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.

Link Prediction

NPGLM: A Non-Parametric Method for Temporal Link Prediction

no code implementations21 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.

Link Prediction

A Hybrid Deep Learning Architecture for Privacy-Preserving Mobile Analytics

1 code implementation8 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.

Privacy Preserving

Recurrent Poisson Factorization for Temporal Recommendation

1 code implementation4 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.

Recommendation Systems

Continuous-Time User Modeling in the Presence of Badges: A Probabilistic Approach

no code implementations7 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.

Point Processes

Spatio-Temporal Modeling of Users' Check-ins in Location-Based Social Networks

no code implementations23 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.

Kissing Cuisines: Exploring Worldwide Culinary Habits on the Web

no code implementations26 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.

Nutrition

HNP3: A Hierarchical Nonparametric Point Process for Modeling Content Diffusion over Social Media

no code implementations2 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.

Point Processes

Predicting Anchor Links between Heterogeneous Social Networks

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

Inferring dynamic diffusion networks in online media

1 code implementation14 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.

MDL-CW: A Multimodal Deep Learning Framework With Cross Weights

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).

Attribute Information Retrieval +4

Active Learning from Positive and Unlabeled Data

1 code implementation24 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.

Active Learning Informativeness +1

A Bayesian Approach to the Data Description Problem

no code implementations24 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.

Patchwise Joint Sparse Tracking with Occlusion Detection

no code implementations5 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.

Local Similarities, Global Coding: An Algorithm for Feature Coding and its Applications

no code implementations24 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.

Spatial-Aware Dictionary Learning for Hyperspectral Image Classification

no code implementations6 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.

Classification Dictionary Learning +2

From Local Similarity to Global Coding: An Application to Image Classification

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.

General Classification Image Classification

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