| 2026 | ICPR | GRASP: Gradient-Aligned Sequential Parameter Transfer for Memory-Efficient Multi-source Learning. | Mary Isabelle Wisell, Nicholas Jacobs, Aayush Manandhar, Salimeh Yasaei Sekeh |
| 2023 | BMVC | Can Deep Networks be Highly Performant, Efficient and Robust simultaneously? | Madan Ravi Ganesh, Salimeh Yasaei Sekeh, Jason J. Corso |
| 2023 | ICLR | Improving Hyperspectral Adversarial Robustness Under Multiple Attacks. | Nicholas Soucy, Salimeh Yasaei Sekeh |
| 2022 | ECCV | Theoretical Understanding of the Information Flow on Continual Learning Performance. | Joshua Andle, Salimeh Yasaei Sekeh |
| 2020 | ICPR | MINT: Deep Network Compression via Mutual Information-based Neuron Trimming. | Madan Ravi Ganesh, Jason J. Corso, Salimeh Yasaei Sekeh |
| 2019 | ICASSP | Feature Selection for Mutlti-labeled Variables via Dependency Maximization. | Salimeh Yasaei Sekeh, Alfred O. Hero III |
| 2018 | ICASSP | A Dimension-Independent Discriminant Between Distributions. | Salimeh Yasaei Sekeh, Brandon Oselio, Alfred O. Hero III |
| 2017 | ICASSP | Information theoretic structure learning with confidence. | Kevin R. Moon, Morteza Noshad, Salimeh Yasaei Sekeh, Alfred O. Hero III |
| 2017 | ISIT | Direct estimation of information divergence using nearest neighbor ratios. | Morteza Noshad, Kevin R. Moon, Salimeh Yasaei Sekeh, Alfred O. Hero III |