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2020 – today
- 2024
[c22]Rune D. Kjærsgaard, Pekka Parviainen, Saket Saurabh, Madhumita Kundu, Line H. Clemmensen:
Fair Soft Clustering. AISTATS 2024: 1270-1278- [c21]Tuukka Korhonen, Fedor V. Fomin, Pekka Parviainen:
Structural perspective on constraint-based learning of Markov networks. AISTATS 2024: 1855-1863 - [c20]Madhumita Kundu, Pekka Parviainen, Saket Saurabh:
Discovering Bayesian Networks when Few Variables Matter. ECAI 2024: 3047-3054 - [c19]Tanmay Inamdar, Madhumita Kundu, Pekka Parviainen, M. S. Ramanujan, Saket Saurabh:
Exponential-Time Approximation Schemes via Compression. ITCS 2024: 64:1-64:22 - [i10]Tuukka Korhonen, Fedor V. Fomin, Pekka Parviainen:
Structural perspective on constraint-based learning of Markov networks. CoRR abs/2403.08562 (2024) - 2023
- [c18]Hyeongji Kim
, Pekka Parviainen, Ketil Malde:
Measuring Adversarial Robustness using a Voronoi-Epsilon Adversary. NLDL 2023 - [c17]Brigt Arve Toppe Håvardstun, Cèsar Ferri, José Hernández-Orallo, Pekka Parviainen, Jan Arne Telle:
XAI with Machine Teaching When Humans Are (Not) Informed About the Irrelevant Features. ECML/PKDD (3) 2023: 378-393 - [i9]Hyeongji Kim, Pekka Parviainen, Terje Berge, Ketil Malde:
Inspecting class hierarchies in classification-based metric learning models. CoRR abs/2301.11065 (2023) - 2022
- [c16]Pierre Gillot, Pekka Parviainen:
Learning Large DAGs by Combining Continuous Optimization and Feedback Arc Set Heuristics. AAAI 2022: 6713-6720 - [c15]Pierre Gillot, Pekka Parviainen:
Convergence of Feedback Arc Set-Based Heuristics for Linear Structural Equation Models. PGM 2022: 157-168 - [i8]Hyeongji Kim, Pekka Parviainen, Ketil Malde:
Distance-Ratio-Based Formulation for Metric Learning. CoRR abs/2201.08676 (2022) - [i7]Johannes Fiedler, Adrià Salvador Palau, Eivind Kristen Osestad, Pekka Parviainen, Bodil Holst:
Realistic mask generation for matter-wave lithography via machine learning. CoRR abs/2207.08723 (2022) - 2021
- [i6]Pierre Gillot, Pekka Parviainen:
Learning Large DAGs by Combining Continuous Optimization and Feedback Arc Set Heuristics. CoRR abs/2107.00571 (2021) - 2020
- [c14]Pierre Gillot, Pekka Parviainen:
Scalable Bayesian Network Structure Learning via Maximum Acyclic Subgraph. PGM 2020: 209-220 - [c13]Topi Talvitie, Pekka Parviainen:
Learning Bayesian Networks with Cops and Robbers. PGM 2020: 473-484
2010 – 2019
- 2019
- [j5]Xiangju Qin, Paul Blomstedt, Eemeli Leppäaho, Pekka Parviainen, Samuel Kaski:
Distributed Bayesian matrix factorization with limited communication. Mach. Learn. 108(10): 1805-1830 (2019) - 2017
- [j4]Pekka Parviainen, Samuel Kaski:
Learning structures of Bayesian networks for variable groups. Int. J. Approx. Reason. 88: 110-127 (2017) - [i5]Xiangju Qin, Paul Blomstedt, Eemeli Leppäaho, Pekka Parviainen, Samuel Kaski:
Distributed Bayesian Matrix Factorization with Minimal Communication. CoRR abs/1703.00734 (2017) - 2016
- [j3]Teppo Niinimaki, Pekka Parviainen, Mikko Koivisto:
Structure Discovery in Bayesian Networks by Sampling Partial Orders. J. Mach. Learn. Res. 17: 57:1-57:47 (2016) - [j2]Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto, Jesper Nederlof, Pekka Parviainen:
Fast Zeta Transforms for Lattices with Few Irreducibles. ACM Trans. Algorithms 12(1): 4:1-4:19 (2016) - [c12]Pekka Parviainen, Samuel Kaski:
Bayesian Networks for Variable Groups. Probabilistic Graphical Models 2016: 380-391 - 2015
- [c11]Indre Zliobaite, Michael Mathioudakis, Tuukka Lehtiniemi, Pekka Parviainen, Tomi Janhunen:
Accessibility by Public Transport Predicts Residential Real Estate Prices: A Case Study in Helsinki Region. MUD@ICML 2015: 65-71 - [c10]Janne H. Korhonen, Pekka Parviainen:
Tractable Bayesian Network Structure Learning with Bounded Vertex Cover Number. NIPS 2015: 622-630 - [i4]Pekka Parviainen, Samuel Kaski:
Bayesian Networks for Variable Groups. CoRR abs/1508.07753 (2015) - 2014
- [c9]Pekka Parviainen, Hossein Shahrabi Farahani, Jens Lagergren:
Learning Bounded Tree-width Bayesian Networks using Integer Linear Programming. AISTATS 2014: 751-759 - 2013
- [j1]Pekka Parviainen, Mikko Koivisto:
Finding optimal Bayesian networks using precedence constraints. J. Mach. Learn. Res. 14(1): 1387-1415 (2013) - [c8]Janne H. Korhonen, Pekka Parviainen:
Exact Learning of Bounded Tree-width Bayesian Networks. AISTATS 2013: 370-378 - 2012
- [b1]Pekka Parviainen:
Algorithms for Exact Structure Discovery in Bayesian Networks. University of Helsinki, Finland, 2012 - [c7]Andreas Björklund, Mikko Koivisto, Thore Husfeldt, Jesper Nederlof, Petteri Kaski, Pekka Parviainen:
Fast zeta transforms for lattices with few irreducibles. SODA 2012: 1436-1444 - [c6]Teppo Niinimaki, Pekka Parviainen:
Local Structure Discovery in Bayesian Networks. UAI 2012: 634-643 - [i3]Teppo Niinimaki, Pekka Parviainen, Mikko Koivisto:
Partial Order MCMC for Structure Discovery in Bayesian Networks. CoRR abs/1202.3753 (2012) - [i2]Pekka Parviainen, Mikko Koivisto:
Exact Structure Discovery in Bayesian Networks with Less Space. CoRR abs/1205.2620 (2012) - [i1]Teppo Niinimaki, Pekka Parviainen:
Local Structure Discovery in Bayesian Networks. CoRR abs/1210.4888 (2012) - 2011
- [c5]Pekka Parviainen, Mikko Koivisto:
Ancestor Relations in the Presence of Unobserved Variables. ECML/PKDD (2) 2011: 581-596 - [c4]Teppo Niinimaki, Pekka Parviainen, Mikko Koivisto:
Partial Order MCMC for Structure Discovery in Bayesian Networks. UAI 2011: 557-564 - 2010
- [c3]Mikko Koivisto, Pekka Parviainen:
A Space-Time Tradeoff for Permutation Problems. SODA 2010: 484-492 - [c2]Pekka Parviainen, Mikko Koivisto:
Bayesian structure discovery in Bayesian networks with less space. AISTATS 2010: 589-596
2000 – 2009
- 2009
- [c1]Pekka Parviainen, Mikko Koivisto:
Exact Structure Discovery in Bayesian Networks with Less Space. UAI 2009: 436-443
Coauthor Index
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