Exact Structure Discovery in Bayesian Networks with Less Space. - Pekka Parviainen; Mikko Koivisto (UAI, 2009)

A Space-Time Tradeoff for Permutation Problems. - Mikko Koivisto; Pekka Parviainen (SODA, 2010)

Bayesian structure discovery in Bayesian networks with less space. - Pekka Parviainen; Mikko Koivisto (AISTATS, 2010)

Ancestor Relations in the Presence of Unobserved Variables. - Pekka Parviainen; Mikko Koivisto (ECML/PKDD (2), 2011)

Partial Order MCMC for Structure Discovery in Bayesian Networks. - Teppo Niinimaki; Pekka Parviainen; Mikko Koivisto (UAI, 2011)

Local Structure Discovery in Bayesian Networks. - Teppo Niinimaki; Pekka Parviainen (UAI, 2012)

Algorithms for Exact Structure Discovery in Bayesian Networks. - Pekka Parviainen (2012)

Exact Learning of Bounded Tree-width Bayesian Networks. - Janne H. Korhonen; Pekka Parviainen (AISTATS, 2013)

Finding optimal Bayesian networks using precedence constraints. - Pekka Parviainen; Mikko Koivisto (J. Mach. Learn. Res., 2013)

Learning Bounded Tree-width Bayesian Networks using Integer Linear Programming. - Pekka Parviainen; Hossein Shahrabi Farahani; Jens Lagergren (AISTATS, 2014)

Accessibility by Public Transport Predicts Residential Real Estate Prices: A Case Study in Helsinki Region. - Indre Zliobaite; Michael Mathioudakis; Tuukka Lehtiniemi; Pekka Parviainen; Tomi Janhunen (MUD@ICML, 2015)

Tractable Bayesian Network Structure Learning with Bounded Vertex Cover Number. - Janne H. Korhonen; Pekka Parviainen (NIPS, 2015)

Bayesian Networks for Variable Groups. - Pekka Parviainen; Samuel Kaski (Probabilistic Graphical Models, 2016)

Structure Discovery in Bayesian Networks by Sampling Partial Orders. - Teppo Niinimaki; Pekka Parviainen; Mikko Koivisto (J. Mach. Learn. Res., 2016)

Fast Zeta Transforms for Lattices with Few Irreducibles. - Andreas Björklund; Thore Husfeldt; Petteri Kaski; Mikko Koivisto; Jesper Nederlof; Pekka Parviainen (ACM Trans. Algorithms, 2016)

Distributed Bayesian Matrix Factorization with Minimal Communication. - Xiangju Qin; Paul Blomstedt; Eemeli Leppäaho; Pekka Parviainen; Samuel Kaski (CoRR, 2017)

Learning structures of Bayesian networks for variable groups. - Pekka Parviainen; Samuel Kaski (Int. J. Approx. Reason., 2017)

Distributed Bayesian matrix factorization with limited communication. - Xiangju Qin; Paul Blomstedt; Eemeli Leppäaho; Pekka Parviainen; Samuel Kaski (Mach. Learn., 2019)

Scalable Bayesian Network Structure Learning via Maximum Acyclic Subgraph. - Pierre Gillot; Pekka Parviainen (PGM, 2020)

Learning Bayesian Networks with Cops and Robbers. - Topi Talvitie; Pekka Parviainen (PGM, 2020)

Learning Large DAGs by Combining Continuous Optimization and Feedback Arc Set Heuristics. - Pierre Gillot; Pekka Parviainen (AAAI, 2022)

Convergence of Feedback Arc Set-Based Heuristics for Linear Structural Equation Models. - Pierre Gillot; Pekka Parviainen (PGM, 2022)

Distance-Ratio-Based Formulation for Metric Learning. - Hyeongji Kim; Pekka Parviainen; Ketil Malde (CoRR, 2022)

Realistic mask generation for matter-wave lithography via machine learning. - Johannes Fiedler; Adrià Salvador Palau; Eivind Kristen Osestad; Pekka Parviainen; Bodil Holst (CoRR, 2022)

Measuring Adversarial Robustness using a Voronoi-Epsilon Adversary. - Hyeongji Kim; Pekka Parviainen; Ketil Malde (NLDL, 2023)

XAI with Machine Teaching When Humans Are (Not) Informed About the Irrelevant Features. - Brigt Arve Toppe Håvardstun; Cèsar Ferri; José Hernández-Orallo; Pekka Parviainen; Jan Arne Telle (ECML/PKDD (3), 2023)

Inspecting class hierarchies in classification-based metric learning models. - Hyeongji Kim; Pekka Parviainen; Terje Berge; Ketil Malde (CoRR, 2023)

Fair Soft Clustering. - Rune D. Kjærsgaard; Pekka Parviainen; Saket Saurabh 001; Madhumita Kundu; Line H. Clemmensen (AISTATS, 2024)

Structural perspective on constraint-based learning of Markov networks. - Tuukka Korhonen; Fedor V. Fomin; Pekka Parviainen (AISTATS, 2024)

Discovering Bayesian Networks when Few Variables Matter. - Madhumita Kundu; Pekka Parviainen; Saket Saurabh 001 (ECAI, 2024)

ProxyDR: Deep Hyperspherical Metric Learning with Distance Ratio-Based Formulation. - Hyeongji Kim; Changkyu Choi; Michael Kampffmeyer; Terje Berge; Pekka Parviainen; Ketil Malde (ECCV Workshops (17), 2024)

Exponential-Time Approximation Schemes via Compression. - Tanmay Inamdar 002; Madhumita Kundu; Pekka Parviainen; M. S. Ramanujan 001; Saket Saurabh 001 (ITCS, 2024)

Time-Approximation Trade-Offs for Learning Bayesian Networks. - Madhumita Kundu; Pekka Parviainen; Saket Saurabh 001 (PGM, 2024)

On Tractability of Learning Bayesian Networks with Ancestral Constraints. - Juha Harviainen; Pekka Parviainen (AISTATS, 2025)