Nikolaos Dimitriadis

Nikolaos Dimitriadis

PhD student

EPFL

Hello! I am Nikos

I am a PhD student in Computer Science at École Polytechnique Fédérale de Lausanne (EPFL), where I am advised by François Fleuret and Pascal Frossard. My research interests revolve around model merging, multi-task and continual learning. I am currently a student researcher at Google.

Before coming to Switzerland, I completed my undergraduate studies in Electrical and Computer Engineering at the National Technical University of Athens in Greece. I conducted my thesis (available here in Greek) at the CVSP lab under the supervision of Petros Maragos. The focus lied on using tropical geometry to analyze Morphological Neural Networks, studying the sparsity of their representations compared to their linear counterparts, their ability to enforce shape constraints such as monotonicity, and extending a training algorithm based on Difference-of-Convex Programming to multiclass problems.

I am also an avid classical guitar player! I love playing Baroque and romantic pieces, such as compositions by Agustín Barrios Mangoré. Check out this beautiful performance!

Download my resumé .

Interests
  • Model Merging
  • Multi-Task Learning
  • Continual Learning
Education
  • PhD in Computer Science

    École Polytechnique Fédérale de Lausanne

  • MEng in Electrical Engineering and Computer Science, 2020

    National Technical University of Athens

Publications

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(2024). Localizing Task Information for Improved Model Merging and Compression. International Conference on Machine Learning (ICML).

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(2024). Pareto Low-Rank Adapters: Efficient Multi-Task Learning with Preferences. arXiv preprint arXiv:2407.08056.

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(2023). Benefits of Max Pooling in Neural Networks: Theoretical and Experimental Evidence. Transactions on Machine Learning Research.

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(2023). Pareto Manifold Learning: Tackling Multiple Tasks via Ensembles of Single-Task Models. International Conference on Machine Learning (ICML).

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(2023). SequeL: A Continual Learning Library in PyTorch and JAX. CVPR Workshop on Continual Learning 2023 (non-archival track).

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(2023). Flexible Channel Dimensions for Differentiable Architecture Search. arXiv (Preprint).

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(2022). U-Boost NAS: Utilization-boosted Differentiable Neural Architecture Search. European Conference on Computer Vision (ECCV).

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(2021). Advances in Morphological Neural Networks: Training, Pruning and Enforcing Shape Constraints. ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

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Contact

nikolaos.dimitriadis[at]epfl.ch