| 2023 | RecSys | Incorporating Time in Sequential Recommendation Models. | Mostafa Rahmani, James Caverlee, Fei Wang |
| 2022 | UAI | Clustering a union of linear subspaces via matrix factorization and innovation search. | Mostafa Rahmani |
| 2021 | ACSSC | Provable Data Clustering via Innovation Search. | Weiwei Li, Mostafa Rahmani, Ping Li |
| 2021 | ACSSC | Non-Local Feature Aggregation on Graphs via Latent Fixed Data Structures. | Mostafa Rahmani, Rasoul Shafipour, Ping Li |
| 2021 | ICASSP | Fast and Provable Robust PCA VIA Normalized Coherence Pursuit. | Mostafa Rahmani, Ping Li |
| 2020 | ICDM | The Necessity of Geometrical Representation for Deep Graph Analysis. | Mostafa Rahmani, Ping Li |
| 2019 | UAI | A Sparse Representation-Based Approach to Linear Regression with Partially Shuffled Labels. | Martin Slawski, Mostafa Rahmani, Ping Li |
| 2018 | ACSSC | Randomized Robust matrix Completion for the Community Detection Problem. | Adel Karimian, Mostafa Rahmani, Andre Beckus, George K. Atia |
| 2018 | ACSSC | Data Dropout in Arbitrary Basis for Deep Network Regularization. | Mostafa Rahmani, George K. Atia |
| 2017 | ICASSP | High dimensional decomposition of coherent/structured matrices via sequential column/row sampling. | Mostafa Rahmani, George K. Atia |
| 2017 | ICML | Coherence Pursuit: Fast, Simple, and Robust Subspace Recovery. | Mostafa Rahmani, George K. Atia |
| 2017 | ICML | Innovation Pursuit: A New Approach to the Subspace Clustering Problem. | Mostafa Rahmani, George K. Atia |
| 2016 | ICML | A Subspace Learning Approach for High Dimensional Matrix Decomposition with Efficient Column/Row Sampling. | Mostafa Rahmani, George K. Atia |
| 2015 | ACSSC | Randomized subspace learning approach for high dimensional low rank plus sparse matrix decomposition. | Mostafa Rahmani, George K. Atia |