Pekka Parviainen

Associate Professor

I am an associate professor in machine learning.

My main research interests lie within probabilistic graphical models, especially in structure learning in Bayesian networks.

List of my publications can be found in my google scholar profile.

Academic article

Show author(s) (2023). Realistic mask generation for matter-wave lithography via machine learning. Machine Learning: Science and Technology.
Show author(s) (2023). Measuring Adversarial Robustness using a Voronoi-Epsilon Adversary. Proceedings of the Northern Lights Deep Learning Workshop. 8 pages.

Show author(s) (2022). Convergence of Feedback Arc Set-Based Heuristics for Linear Structural Equation Models. Proceedings of Machine Learning Research (PMLR). 157-168.

Show author(s) (2020). Scalable Bayesian Network Structure Learning via Maximum Acyclic Subgraph. Proceedings of Machine Learning Research (PMLR). 209-220.
Show author(s) (2020). Learning Bayesian Networks with Cops and Robbers. Proceedings of Machine Learning Research (PMLR). 473-484.

Show author(s) (2019). Distributed Bayesian matrix factorization with limited communication. Machine Learning. 1805-1830.

Academic lecture

Show author(s) (2023). Measuring Adversarial Robustness using a Voronoi-Epsilon Adversary.

Doctoral dissertation

Academic chapter/article/Conference paper

Show author(s) (2023). XAI with Machine Teaching When Humans Are (Not) Informed About the Irrelevant Features. 16 pages.

Show author(s) (2022). Learning Large DAGs by Combining Continuous Optimization and Feedback Arc Set Heuristics. 8 pages.