Amjad Seyedi

Publications

Preprints

• Supervised Deep Multimodal Matrix Factorization for Interpretable Brain Network Analysis
  A. Seyedi, Lifang He, Songlin Zhao, Akwum Onwunta, and Nicolas Gillis.

• ECG-NAT: A Self-supervised Neighborhood Attention Transformer for Multi-lead ECG Classification
  M. Gazeran, S. Soleymanbaigi, F. Daneshfar, A. Seyedi, and F. Akhlaghian.

2026

• Bilinear Nonnegative Matrix Factorization for Hyperspectral Unmixing – [source code]
  A. Seyedi, A. Vandaele, and N. Gillis, European Signal Processing Conference 2026.

• Robust Asymmetric Encoder-Decoder Nonnegative Matrix Factorization for Hyperspectral Anomaly Detection – [source code]
  S. Moradi, A. Seyedi, W. Barkhoda, and F. Akhlaghian, Neurocomputing 2026.

• Robust log-based multi-label feature selection with dynamic label correlation and relevance–redundancy optimization– [source code]
  M. Faraji, A. Seyedi, and F. Akhlaghian, Knowledge-Based Systems 2026.

• Contrastive Calibration on Consensus and Complementary Multi-View Representations – [source code]
  N. Jabari, A. Seyedi, R. Mahmoodi, and F. Akhlaghian, Pattern Recognition 2026.

• Encoder-Decoder Symmetric Nonnegative Matrix Tri-Factorization for Graph Clustering– [source code]
  A. Seyedi and N. Gillis, International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2026.

• Semantic Encoder-Decoder Nonnegative Matrix Factorization with Kullback-Leibler Divergence
  S. Soleymanbaigi, A. Seyedi, F. Daneshfar, and F. Akhlaghian, International Journal of Machine Learning and Cybernetics 2026.

• Community Detection via Deep Motif-regularized Asymmetric Nonnegative Matrix Factorization – [source code]
  H. Sohrabi, A. Seyedi, P. Moradi, and S. Esmaeili, Engineering Applications of Artificial Intelligence 2026.

• Distributionally Robust Nonnegative Matrix Factorization with Self-Paced Adaptive Multi-Loss Fusion – [source code]
  W. Barkhoda, A. Seyedi, N. Gillis, and F. Akhlaghian, Information Sciences 2026.

• Encoder-Decoder Nonnegative Matrix Factorization with β-Divergence for Data Clustering
  S. Soleymanbaigi, A. Seyedi, F. Akhlaghian, and F. Daneshfar, Pattern Recognition 2026.

• Instance-wise Distributionally Robust Nonnegative Matrix Factorization– [source code]
  W. Barkhoda, A. Seyedi, N. Gillis, and F. Akhlaghian, Pattern Recognition 2026.

2025

• A Deep Latent Factor Graph Clustering with Fairness-Utility Trade-off Perspective – [source code] [pdf]
  S. Ghodsi, A. Seyedi, T. Quy, F. Karimi, and E. Ntoutsi, 2025 IEEE International Conference on Big Data.

• A New Bi-Level Deep Human Action Representation Structure based on the Sequence of Sub-Actions
  F. Akhlaghian, M. Ramezani, H. Afshoon, A. Seyedi, and A. Moradyani, Neural Computing and Applications 2025.

2024

• Diverse Joint Nonnegative Matrix Tri-Factorization for Attributed Graph Clustering
  A. Mohammadi, A. Seyedi, F. Akhlaghian, and R. Pir Mohammadiani, Applied Soft Computing 2024.

• Enhancing Link Prediction through Adversarial Training in Deep Nonnegative Matrix Factorization
  R. Mahmoodi, A. Seyedi, A. Abdollahpouri, and F. Akhlaghian, Engineering Applications of Artificial Intelligence 2024.

• Towards Cohesion-Fairness Harmony: Contrastive Regularization in Individual Fair Graph Clustering – [source code] [pdf]
  S. Ghodsi, A. Seyedi, and E. Ntoutsi, Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2024.

• Unsupervised Feature Selection using Orthogonal Encoder-Decoder Factorization
  M. Mozafari, A. Seyedi, R. Pir Mohammadiani, and F. Akhlaghian, Information Sciences 2024.

• Multi-Label Feature Selection with Global and Local Label Correlation
  M. Faraji, A. Seyedi, F. Akhlaghian, and R. Mahmoodi, Expert Systems with Applications 2024.

• Deep Asymmetric Nonnegative Matrix Factorization for Graph Clustering
  A. Hajiveiseh, A. Seyedi, and F. Akhlaghian, Pattern Recognition 2024.

2023

• Link Prediction by Adversarial Nonnegative Matrix Factorization
  R. Mahmoodi, A. Seyedi, F. Akhlaghian, and A. Abdollahpouri, Knowledge-Based Systems 2023.

• Self-Supervised Semi-Supervised Nonnegative Matrix Factorization for Data Clustering – [source code]
  J. Chavoshinejad, A. Seyedi, F. Akhlaghian, and N. Salahian, Pattern Recognition 2023.

• Elastic Adversarial Deep Nonnegative Matrix Factorization for Matrix Completion – [source code]
  A. Seyedi, F. Akhlaghian, A. Lotfi, N. Salahian, and J. Chavoshinejad, Information Sciences 2023.

• Deep Autoencoder-like NMF with Contrastive Regularization and Feature Relationship Preservation – [source code]
  N. Salahian, F. Akhlaghian, A. Seyedi, and J. Chavoshinejad, Expert Systems with Applications 2023.

2020

• Asymmetric Semi-Nonnegative Matrix Factorization for Directed Graph Clustering – [source code]
  R. Abdollahi, A. Seyedi, and M.R. Noorimehr, IEEE International Conference on Computer and Knowledge Engineering (ICCKE) 2020.

2019

• Self-Paced Multi-Label Learning with Diversity – [source code] [pdf]
  A. Seyedi, S. Ghodsi, F. Akhlaghian, M. Jalili, and P. Moradi, Asian Conference on Machine Learning (ACML) 2019.

• Dynamic Graph-based Label Propagation for Density Peaks Clustering – [source code]
  A. Seyedi, A. Lotfi, P. Moradi, and N.N. Qader, Expert Systems with Applications 2019.

2017

• A Weakly-Supervised Factorization Method with Dynamic Graph Embedding
  A. Seyedi, P. Moradi, and F. Akhlaghian Tab, IEEE Artificial Intelligence and Signal Processing Conference (AISP) 2017.

• A Clustering-based Matrix Factorization Method to Improve the Accuracy of Recommendation Systems
  Z. Shajarian, A. Seyedi, and P. Moradi, IEEE Iranian Conference on Electrical Engineering (ICEE) 2017.

2016

• An Improved Density Peaks Method for Data Clustering – [source code]
  A. Lotfi, A. Seyedi, and P. Moradi, IEEE International Conference on Computer and Knowledge Engineering (ICCKE) 2016.

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