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ORCIDMikko Koivisto
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- affiliation: University of Helsinki, Finland
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2020 – today
- 2024
[j22]Topi Talvitie, Mikko Koivisto:
Approximate Counting of Linear Extensions in Practice. J. Artif. Intell. Res. 81: 643-681 (2024)- [c62]Juha Harviainen, Mikko Koivisto:
Estimating the Permanent by Nesting Importance Sampling. ICML 2024 - 2023
- [c61]Juha Harviainen
, Mikko Koivisto:
A Faster Practical Approximation Scheme for the Permanent. AAAI 2023: 12216-12224 - [c60]Juha Harviainen, Mikko Koivisto:
Revisiting Bayesian network learning with small vertex cover. UAI 2023: 819-828 - [c59]Juha Harviainen, Vaidyanathan Peruvemba Ramaswamy, Mikko Koivisto:
On inference and learning with probabilistic generating circuits. UAI 2023: 829-838 - [i25]Juha Harviainen, Kseniya Rychkova, Mikko Koivisto:
Quantum Speedups for Bayesian Network Structure Learning. CoRR abs/2305.19673 (2023) - 2022
- [c58]Juha Harviainen, Mikko Koivisto, Petteri Kaski:
Trustworthy Monte Carlo. NeurIPS 2022 - 2021
- [c57]Juha Harviainen, Antti Röyskö, Mikko Koivisto:
Approximating the Permanent with Deep Rejection Sampling. NeurIPS 2021: 213-224 - [i24]Juha Harviainen, Antti Röyskö, Mikko Koivisto:
Approximating the Permanent with Deep Rejection Sampling. CoRR abs/2108.07359 (2021) - 2020
- [j21]Kustaa Kangas, Mikko Koivisto, Sami Salonen:
A Faster Tree-Decomposition Based Algorithm for Counting Linear Extensions. Algorithmica 82(8): 2156-2173 (2020) - [j20]Mikko Koivisto, Petteri Laakkonen, Juho Lauri:
NP-completeness results for partitioning a graph into total dominating sets. Theor. Comput. Sci. 818: 22-31 (2020) - [c56]Johan Pensar, Topi Talvitie, Antti Hyttinen, Mikko Koivisto:
A Bayesian Approach for Estimating Causal Effects from Observational Data. AAAI 2020: 5395-5402 - [c55]Negin Karimi, Petteri Kaski, Mikko Koivisto:
Error-Correcting and Verifiable Parallel Inference in Graphical Models. AAAI 2020: 10194-10201 - [c54]Jussi Viinikka, Antti Hyttinen, Johan Pensar, Mikko Koivisto:
Towards Scalable Bayesian Learning of Causal DAGs. NeurIPS 2020 - [c53]Mikko Koivisto, Antti Röyskö:
Fast Multi-Subset Transform and Weighted Sums over Acyclic Digraphs. SWAT 2020: 29:1-29:12 - [c52]Jussi Viinikka, Mikko Koivisto:
Layering-MCMC for Structure Learning in Bayesian Networks. UAI 2020: 839-848 - [i23]Mikko Koivisto, Antti Röyskö:
Fast Multi-Subset Transform and Weighted Sums Over Acyclic Digraphs. CoRR abs/2002.08475 (2020) - [i22]Jussi Viinikka, Antti Hyttinen, Johan Pensar, Mikko Koivisto:
Towards Scalable Bayesian Learning of Causal DAGs. CoRR abs/2010.00684 (2020)
2010 – 2019
- 2019
- [j19]Topi Talvitie, Ralf Eggeling, Mikko Koivisto:
Learning Bayesian networks with local structure, mixed variables, and exact algorithms. Int. J. Approx. Reason. 115: 69-95 (2019) - [j18]Ralf Eggeling, Ivo Grosse, Mikko Koivisto:
Algorithms for learning parsimonious context trees. Mach. Learn. 108(6): 879-911 (2019) - [c51]Topi Talvitie, Mikko Koivisto:
Counting and Sampling Markov Equivalent Directed Acyclic Graphs. AAAI 2019: 7984-7991 - [c50]Ralf Eggeling, Jussi Viinikka, Aleksis Vuoksenmaa, Mikko Koivisto:
On Structure Priors for Learning Bayesian Networks. AISTATS 2019: 1687-1695 - [c49]Topi Talvitie, Aleksis Vuoksenmaa, Mikko Koivisto:
Exact Sampling of Directed Acyclic Graphs from Modular Distributions. UAI 2019: 965-974 - 2018
- [j17]Kustaa Kangas, Petteri Kaski, Janne H. Korhonen, Mikko Koivisto:
On the Number of Connected Sets in Bounded Degree Graphs. Electron. J. Comb. 25(4): 4 (2018) - [j16]Brandon M. Malone, Kustaa Kangas, Matti Järvisalo, Mikko Koivisto, Petri Myllymäki:
Empirical hardness of finding optimal Bayesian network structures: algorithm selection and runtime prediction. Mach. Learn. 107(1): 247-283 (2018) - [j15]Per Austrin, Petteri Kaski, Mikko Koivisto, Jesper Nederlof:
Sharper Upper Bounds for Unbalanced Uniquely Decodable Code Pairs. IEEE Trans. Inf. Theory 64(2): 1368-1373 (2018) - [c48]Topi Talvitie, Kustaa Kangas, Teppo Mikael Niinimäki, Mikko Koivisto:
Counting Linear Extensions in Practice: MCMC Versus Exponential Monte Carlo. AAAI 2018: 1431-1438 - [c47]Jussi Viinikka, Ralf Eggeling, Mikko Koivisto:
Intersection-Validation: A Method for Evaluating Structure Learning without Ground Truth. AISTATS 2018: 1570-1578 - [c46]Topi Talvitie, Kustaa Kangas, Teppo Mikael Niinimäki, Mikko Koivisto:
A Scalable Scheme for Counting Linear Extensions. IJCAI 2018: 5119-5125 - [c45]Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto:
Counting Connected Subgraphs with Maximum-Degree-Aware Sieving. ISAAC 2018: 17:1-17:12 - [c44]Kustaa Kangas, Mikko Koivisto, Sami Salonen:
A Faster Tree-Decomposition Based Algorithm for Counting Linear Extensions. IPEC 2018: 5:1-5:13 - [c43]Topi Talvitie, Ralf Eggeling, Mikko Koivisto:
Finding Optimal Bayesian Networks with Local Structure. PGM 2018: 451-462 - 2017
- [j14]Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto:
Narrow sieves for parameterized paths and packings. J. Comput. Syst. Sci. 87: 119-139 (2017) - [c42]Mikko Koivisto, Petteri Laakkonen, Juho Lauri:
NP-completeness Results for Partitioning a Graph into Total Dominating Sets. COCOON 2017: 333-345 - [c41]Topi Talvitie, Teppo Mikael Niinimäki, Mikko Koivisto:
The Mixing of Markov Chains on Linear Extensions in Practice. IJCAI 2017: 524-530 - [i21]Brandon M. Malone, Kustaa Kangas, Matti Järvisalo, Mikko Koivisto, Petri Myllymäki:
AS-ASL: Algorithm Selection with Auto-sklearn. OASC 2017: 19-22 - 2016
- [j13]Magnus Find, Mika Göös, Matti Järvisalo, Petteri Kaski, Mikko Koivisto, Janne H. Korhonen:
Separating OR, SUM, and XOR circuits. J. Comput. Syst. Sci. 82(5): 793-801 (2016) - [j12]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) - [j11]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) - [c40]Kustaa Kangas, Teemu Hankala, Teppo Mikael Niinimäki, Mikko Koivisto:
Counting Linear Extensions of Sparse Posets. IJCAI 2016: 603-609 - [c39]Per Austrin, Petteri Kaski, Mikko Koivisto, Jesper Nederlof:
Sharper upper bounds for unbalanced Uniquely Decodable Code Pairs. ISIT 2016: 335-339 - [c38]Per Austrin, Petteri Kaski, Mikko Koivisto, Jesper Nederlof:
Dense Subset Sum May Be the Hardest. STACS 2016: 13:1-13:14 - [c37]Ralf Eggeling, Mikko Koivisto:
Pruning Rules for Learning Parsimonious Context Trees. UAI 2016 - [i20]Per Austrin, Petteri Kaski, Mikko Koivisto, Jesper Nederlof:
Sharper Upper Bounds for Unbalanced Uniquely Decodable Code Pairs. CoRR abs/1605.00462 (2016) - 2015
- [j10]Serge Gaspers, Mikko Koivisto, Mathieu Liedloff, Sebastian Ordyniak, Stefan Szeider:
On finding optimal polytrees. Theor. Comput. Sci. 592: 49-58 (2015) - [c36]Ralf Eggeling, Mikko Koivisto, Ivo Grosse:
Dealing with small data: On the generalization of context trees. ICML 2015: 1245-1253 - [c35]Per Austrin, Petteri Kaski, Mikko Koivisto, Jesper Nederlof:
Subset Sum in the Absence of Concentration. STACS 2015: 48-61 - [c34]Kustaa Kangas, Teppo Mikael Niinimäki, Mikko Koivisto:
Averaging of Decomposable Graphs by Dynamic Programming and Sampling. UAI 2015: 415-424 - [i19]Per Austrin, Mikko Koivisto, Petteri Kaski, Jesper Nederlof:
Dense Subset Sum may be the hardest. CoRR abs/1508.06019 (2015) - 2014
- [j9]Petteri Kaski, Mikko Koivisto, Janne H. Korhonen, Igor S. Sergeev:
Fast monotone summation over disjoint sets. Inf. Process. Lett. 114(5): 264-267 (2014) - [c33]Brandon M. Malone, Kustaa Kangas, Matti Järvisalo, Mikko Koivisto, Petri Myllymäki:
Predicting the Hardness of Learning Bayesian Networks. AAAI 2014: 2460-2466 - [c32]Kustaa Kangas, Mikko Koivisto, Teppo Mikael Niinimäki:
Learning Chordal Markov Networks by Dynamic Programming. NIPS 2014: 2357-2365 - [c31]Kustaa Kangas, Petteri Kaski, Mikko Koivisto, Janne H. Korhonen:
On the Number of Connected Sets in Bounded Degree Graphs. WG 2014: 336-347 - 2013
- [j8]Pekka Parviainen, Mikko Koivisto:
Finding optimal Bayesian networks using precedence constraints. J. Mach. Learn. Res. 14(1): 1387-1415 (2013) - [c30]Per Austrin, Petteri Kaski, Mikko Koivisto, Jussi Määttä:
Space-Time Tradeoffs for Subset Sum: An Improved Worst Case Algorithm. ICALP (1) 2013: 45-56 - [c29]Teppo Mikael Niinimäki, Mikko Koivisto:
Annealed Importance Sampling for Structure Learning in Bayesian Networks. IJCAI 2013: 1579-1585 - [c28]Teppo Niinimaki, Mikko Koivisto:
Treedy: A Heuristic for Counting and Sampling Subsets. UAI 2013 - [i18]Per Austrin, Petteri Kaski, Mikko Koivisto, Jussi Määttä:
Space--Time Tradeoffs for Subset Sum: An Improved Worst Case Algorithm. CoRR abs/1303.0609 (2013) - [i17]Magnus Find, Mika Göös, Matti Järvisalo, Petteri Kaski, Mikko Koivisto, Janne H. Korhonen:
Separating OR, SUM, and XOR Circuits. CoRR abs/1304.0513 (2013) - [i16]Teppo Niinimaki, Mikko Koivisto:
Treedy: A Heuristic for Counting and Sampling Subsets. CoRR abs/1309.6851 (2013) - 2012
- [j7]Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto:
The traveling salesman problem in bounded degree graphs. ACM Trans. Algorithms 8(2): 18:1-18:13 (2012) - [c27]Serge Gaspers, Mikko Koivisto, Mathieu Liedloff, Sebastian Ordyniak, Stefan Szeider:
On Finding Optimal Polytrees. AAAI 2012: 750-756 - [c26]Petteri Kaski, Mikko Koivisto, Jesper Nederlof:
Homomorphic Hashing for Sparse Coefficient Extraction. IPEC 2012: 147-158 - [c25]Petteri Kaski, Mikko Koivisto, Janne H. Korhonen:
Fast Monotone Summation over Disjoint Sets. IPEC 2012: 159-170 - [c24]Matti Järvisalo, Petteri Kaski, Mikko Koivisto, Janne H. Korhonen:
Finding Efficient Circuits for Ensemble Computation. SAT 2012: 369-382 - [c23]Andreas Björklund, Mikko Koivisto, Thore Husfeldt, Jesper Nederlof, Petteri Kaski, Pekka Parviainen:
Fast zeta transforms for lattices with few irreducibles. SODA 2012: 1436-1444 - [i15]Teppo Niinimaki, Pekka Parviainen, Mikko Koivisto:
Partial Order MCMC for Structure Discovery in Bayesian Networks. CoRR abs/1202.3753 (2012) - [i14]Petteri Kaski, Mikko Koivisto, Jesper Nederlof:
Homomorphic Hashing for Sparse Coefficient Extraction. CoRR abs/1203.4063 (2012) - [i13]Pekka Parviainen, Mikko Koivisto:
Exact Structure Discovery in Bayesian Networks with Less Space. CoRR abs/1205.2620 (2012) - [i12]Mikko Koivisto:
Advances in exact Bayesian structure discovery in Bayesian networks. CoRR abs/1206.6828 (2012) - [i11]Petteri Kaski, Mikko Koivisto, Janne H. Korhonen:
Fast Monotone Summation over Disjoint Sets. CoRR abs/1208.0554 (2012) - [i10]Serge Gaspers, Mikko Koivisto, Mathieu Liedloff, Sebastian Ordyniak, Stefan Szeider:
On Finding Optimal Polytrees. CoRR abs/1208.1692 (2012) - 2011
- [j6]Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto:
Covering and packing in linear space. Inf. Process. Lett. 111(21-22): 1033-1036 (2011) - [c22]Pekka Parviainen, Mikko Koivisto:
Ancestor Relations in the Presence of Unobserved Variables. ECML/PKDD (2) 2011: 581-596 - [c21]Teppo Niinimaki, Pekka Parviainen, Mikko Koivisto:
Partial Order MCMC for Structure Discovery in Bayesian Networks. UAI 2011: 557-564 - 2010
- [j5]Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto:
Evaluation of permanents in rings and semirings. Inf. Process. Lett. 110(20): 867-870 (2010) - [j4]Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto:
Trimmed Moebius Inversion and Graphs of Bounded Degree. Theory Comput. Syst. 47(3): 637-654 (2010) - [c20]Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto:
Covering and Packing in Linear Space. ICALP (1) 2010: 727-737 - [c19]Mikko Koivisto, Pekka Parviainen:
A Space-Time Tradeoff for Permutation Problems. SODA 2010: 484-492 - [c18]Pekka Parviainen, Mikko Koivisto:
Bayesian structure discovery in Bayesian networks with less space. AISTATS 2010: 589-596 - [i9]Mikko Koivisto, Valentin Polishchuk:
Geodesic diameter of a polygonal domain in O(n^4 log n) time. CoRR abs/1006.1998 (2010) - [i8]Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto:
Narrow sieves for parameterized paths and packings. CoRR abs/1007.1161 (2010)
2000 – 2009
- 2009
- [j3]Andreas Björklund, Thore Husfeldt, Mikko Koivisto:
Set Partitioning via Inclusion-Exclusion. SIAM J. Comput. 39(2): 546-563 (2009) - [c17]Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto:
Counting Paths and Packings in Halves. ESA 2009: 578-586 - [c16]Mikko Koivisto:
Partitioning into Sets of Bounded Cardinality. IWPEC 2009: 258-263 - [c15]Pekka Parviainen, Mikko Koivisto:
Exact Structure Discovery in Bayesian Networks with Less Space. UAI 2009: 436-443 - [i7]Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto:
Counting Paths and Packings in Halves. CoRR abs/0904.3093 (2009) - [i6]Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto:
On evaluation of permanents. CoRR abs/0904.3251 (2009) - 2008
- [c14]Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto:
Computing the Tutte Polynomial in Vertex-Exponential Time. FOCS 2008: 677-686 - [c13]Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto:
The Travelling Salesman Problem in Bounded Degree Graphs. ICALP (1) 2008: 198-209 - [c12]Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto:
Trimmed Moebius Inversion and Graphs of Bounded Degree. STACS 2008: 85-96 - [c11]Pasi Rastas, Jussi Kollin, Mikko Koivisto:
Fast Bayesian Haplotype Inference Via Context Tree Weighting. WABI 2008: 259-270 - [i5]Fedor V. Fomin, Kazuo Iwama, Dieter Kratsch, Petteri Kaski, Mikko Koivisto, Lukasz Kowalik, Yoshio Okamoto, Johan M. M. van Rooij, Ryan Williams:
08431 Open Problems - Moderately Exponential Time Algorithms. Moderately Exponential Time Algorithms 2008 - [i4]Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto:
Trimmed Moebius Inversion and Graphs of Bounded Degree. CoRR abs/0802.2834 (2008) - [i3]Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto:
The fast intersection transform with applications to counting paths. CoRR abs/0809.2489 (2008) - 2007
- [c10]Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto:
Fourier meets möbius: fast subset convolution. STOC 2007: 67-74 - [i2]Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto:
Computing the Tutte polynomial in vertex-exponential time. CoRR abs/0711.2585 (2007) - 2006
- [j2]Mikko Koivisto:
Optimal 2-constraint satisfaction via sum-product algorithms. Inf. Process. Lett. 98(1): 24-28 (2006) - [c9]Mikko Koivisto:
Parent Assignment Is Hard for the MDL, AIC, and NML Costs. COLT 2006: 289-303 - [c8]Jussi Kollin, Mikko Koivisto:
Bayesian Learning with Mixtures of Trees. ECML 2006: 294-305 - [c7]Mikko Koivisto:
An O*(2^n ) Algorithm for Graph Coloring and Other Partitioning Problems via Inclusion--Exclusion. FOCS 2006: 583-590 - [c6]Mikko Koivisto:
Advances in Exact Bayesian Structure Discovery in Bayesian Networks. UAI 2006 - [i1]Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto:
Fourier meets Möbius: fast subset convolution. CoRR abs/cs/0611101 (2006) - 2005
- [c5]Mikko Koivisto, Kismat Sood:
Computational aspects of Bayesian partition models. ICML 2005: 433-440 - [c4]Pasi Rastas, Mikko Koivisto, Heikki Mannila, Esko Ukkonen:
A Hidden Markov Technique for Haplotype Reconstruction. WABI 2005: 140-151 - 2004
- [j1]Mikko Koivisto, Kismat Sood:
Exact Bayesian Structure Discovery in Bayesian Networks. J. Mach. Learn. Res. 5: 549-573 (2004) - [c3]Mikko Koivisto, Teemu Kivioja, Heikki Mannila, Pasi Rastas, Esko Ukkonen:
Hidden Markov Modelling Techniques for Haplotype Analysis. ALT 2004: 37-52 - [c2]Mikko Koivisto, Pasi Rastas, Esko Ukkonen:
Recombination Systems. Theory Is Forever 2004: 159-169 - 2003
- [c1]Mikko Koivisto, Markus Perola, T. Varilo, W. Hennah, J. Ekelund, Margus Lukk, L. Peltonen, Esko Ukkonen, Heikki Mannila:
An MDL Method for Finding Haplotype Blocks and for Estimating the Strength of Haplotype Block Boundaries. Pacific Symposium on Biocomputing 2003: 502-513
Coauthor Index
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