Mikko Koivisto

112 papers A* 23A 20B 7C 2Misc 2Journal 46Unranked 12

Year	Rank	Type	Title / Venue / Authors
2025	A	`conf`	Quantum Speedups for Bayesian Network Structure Learning. UAI Juha Harviainen, Kseniya Rychkova, Mikko Koivisto
2025	J	`jnl`	Scaling Up Bayesian DAG Sampling. CoRR Daniele Nikzad, Alexander Zhilkin, Juha Harviainen, Jack Kuipers, Giusi Moffa, Mikko Koivisto
2024	J	`jnl`	Approximate Counting of Linear Extensions in Practice. J. Artif. Intell. Res. Topi Talvitie, Mikko Koivisto
2024	A*	`conf`	Estimating the Permanent by Nesting Importance Sampling. ICML Juha Harviainen, Mikko Koivisto
2024	A	`conf`	Faster Perfect Sampling of Bayesian Network Structures. UAI Juha Harviainen, Mikko Koivisto
2023	A*	`conf`	A Faster Practical Approximation Scheme for the Permanent. AAAI Juha Harviainen, Mikko Koivisto
2023	A	`conf`	On inference and learning with probabilistic generating circuits. UAI Juha Harviainen, Vaidyanathan Peruvemba Ramaswamy, Mikko Koivisto
2023	J	`jnl`	Quantum Speedups for Bayesian Network Structure Learning. CoRR Juha Harviainen, Kseniya Rychkova, Mikko Koivisto
2023	A	`conf`	Revisiting Bayesian network learning with small vertex cover. UAI Juha Harviainen, Mikko Koivisto
2022	A*	`conf`	Trustworthy Monte Carlo. NeurIPS Juha Harviainen, Mikko Koivisto, Petteri Kaski
2021	A*	`conf`	Approximating the Permanent with Deep Rejection Sampling. NeurIPS Juha Harviainen, Antti Röyskö, Mikko Koivisto
2021	J	`jnl`	Approximating the Permanent with Deep Rejection Sampling. CoRR Juha Harviainen, Antti Röyskö, Mikko Koivisto
2020	A*	`conf`	A Bayesian Approach for Estimating Causal Effects from Observational Data. AAAI Johan Pensar, Topi Talvitie, Antti Hyttinen, Mikko Koivisto
2020	J	`jnl`	A Faster Tree-Decomposition Based Algorithm for Counting Linear Extensions. Algorithmica Kustaa Kangas, Mikko Koivisto, Sami Salonen
2020	A*	`conf`	Error-Correcting and Verifiable Parallel Inference in Graphical Models. AAAI Negin Karimi, Petteri Kaski, Mikko Koivisto
2020	J	`jnl`	Fast Multi-Subset Transform and Weighted Sums Over Acyclic Digraphs. CoRR Mikko Koivisto, Antti Röyskö
2020	—	`conf`	Fast Multi-Subset Transform and Weighted Sums over Acyclic Digraphs. SWAT Mikko Koivisto, Antti Röyskö
2020	A	`conf`	Layering-MCMC for Structure Learning in Bayesian Networks. UAI Jussi Viinikka, Mikko Koivisto
2020	J	`jnl`	NP-completeness results for partitioning a graph into total dominating sets. Theor. Comput. Sci. Mikko Koivisto, Petteri Laakkonen, Juho Lauri
2020	A*	`conf`	Towards Scalable Bayesian Learning of Causal DAGs. NeurIPS Jussi Viinikka, Antti Hyttinen, Johan Pensar, Mikko Koivisto
2020	J	`jnl`	Towards Scalable Bayesian Learning of Causal DAGs. CoRR Jussi Viinikka, Antti Hyttinen, Johan Pensar, Mikko Koivisto
2019	J	`jnl`	Algorithms for learning parsimonious context trees. Mach. Learn. Ralf Eggeling, Ivo Grosse, Mikko Koivisto
2019	A*	`conf`	Counting and Sampling Markov Equivalent Directed Acyclic Graphs. AAAI Topi Talvitie, Mikko Koivisto
2019	A	`conf`	Exact Sampling of Directed Acyclic Graphs from Modular Distributions. UAI Topi Talvitie, Aleksis Vuoksenmaa, Mikko Koivisto
2019	J	`jnl`	Learning Bayesian networks with local structure, mixed variables, and exact algorithms. Int. J. Approx. Reason. Topi Talvitie, Ralf Eggeling, Mikko Koivisto
2019	A	`conf`	On Structure Priors for Learning Bayesian Networks. AISTATS Ralf Eggeling, Jussi Viinikka, Aleksis Vuoksenmaa, Mikko Koivisto
2018	B	`conf`	A Faster Tree-Decomposition Based Algorithm for Counting Linear Extensions. IPEC Kustaa Kangas, Mikko Koivisto, Sami Salonen
2018	A*	`conf`	A Scalable Scheme for Counting Linear Extensions. IJCAI Topi Talvitie, Kustaa Kangas, Teppo Mikael Niinimäki, Mikko Koivisto
2018	B	`conf`	Counting Connected Subgraphs with Maximum-Degree-Aware Sieving. ISAAC Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto
2018	A*	`conf`	Counting Linear Extensions in Practice: MCMC Versus Exponential Monte Carlo. AAAI Topi Talvitie, Kustaa Kangas, Teppo Mikael Niinimäki, Mikko Koivisto
2018	J	`jnl`	Empirical hardness of finding optimal Bayesian network structures: algorithm selection and runtime prediction. Mach. Learn. Brandon M. Malone, Kustaa Kangas, Matti Järvisalo, Mikko Koivisto, Petri Myllymäki
2018	—	`conf`	Finding Optimal Bayesian Networks with Local Structure. PGM Topi Talvitie, Ralf Eggeling, Mikko Koivisto
2018	A	`conf`	Intersection-Validation: A Method for Evaluating Structure Learning without Ground Truth. AISTATS Jussi Viinikka, Ralf Eggeling, Mikko Koivisto
2018	J	`jnl`	On the Number of Connected Sets in Bounded Degree Graphs. Electron. J. Comb. Kustaa Kangas, Petteri Kaski, Janne H. Korhonen, Mikko Koivisto
2018	J	`jnl`	Sharper Upper Bounds for Unbalanced Uniquely Decodable Code Pairs. IEEE Trans. Inf. Theory Per Austrin, Petteri Kaski, Mikko Koivisto, Jesper Nederlof
2017	—	`conf`	AS-ASL: Algorithm Selection with Auto-sklearn. OASC Brandon M. Malone, Kustaa Kangas, Matti Järvisalo, Mikko Koivisto, Petri Myllymäki
2017	Misc	`conf`	NP-completeness Results for Partitioning a Graph into Total Dominating Sets. COCOON Mikko Koivisto, Petteri Laakkonen, Juho Lauri
2017	J	`jnl`	Narrow sieves for parameterized paths and packings. J. Comput. Syst. Sci. Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto
2017	A*	`conf`	The Mixing of Markov Chains on Linear Extensions in Practice. IJCAI Topi Talvitie, Teppo Mikael Niinimäki, Mikko Koivisto
2016	A*	`conf`	Counting Linear Extensions of Sparse Posets. IJCAI Kustaa Kangas, Teemu Hankala, Teppo Mikael Niinimäki, Mikko Koivisto
2016	A	`conf`	Dense Subset Sum May Be the Hardest. STACS Per Austrin, Petteri Kaski, Mikko Koivisto, Jesper Nederlof
2016	J	`jnl`	Fast Zeta Transforms for Lattices with Few Irreducibles. ACM Trans. Algorithms Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto, Jesper Nederlof, Pekka Parviainen
2016	A	`conf`	Pruning Rules for Learning Parsimonious Context Trees. UAI Ralf Eggeling, Mikko Koivisto
2016	J	`jnl`	Separating OR, SUM, and XOR circuits. J. Comput. Syst. Sci. Magnus Find, Mika Göös, Matti Järvisalo, Petteri Kaski, Mikko Koivisto, Janne H. Korhonen
2016	J	`jnl`	Sharper Upper Bounds for Unbalanced Uniquely Decodable Code Pairs. CoRR Per Austrin, Petteri Kaski, Mikko Koivisto, Jesper Nederlof
2016	B	`conf`	Sharper upper bounds for unbalanced Uniquely Decodable Code Pairs. ISIT Per Austrin, Petteri Kaski, Mikko Koivisto, Jesper Nederlof
2016	J	`jnl`	Structure Discovery in Bayesian Networks by Sampling Partial Orders. J. Mach. Learn. Res. Teppo Niinimaki, Pekka Parviainen, Mikko Koivisto
2015	A	`conf`	Averaging of Decomposable Graphs by Dynamic Programming and Sampling. UAI Kustaa Kangas, Teppo Mikael Niinimäki, Mikko Koivisto
2015	A*	`conf`	Dealing with small data: On the generalization of context trees. ICML Ralf Eggeling, Mikko Koivisto, Ivo Grosse
2015	J	`jnl`	Dense Subset Sum may be the hardest. CoRR Per Austrin, Mikko Koivisto, Petteri Kaski, Jesper Nederlof
2015	J	`jnl`	On finding optimal polytrees. Theor. Comput. Sci. Serge Gaspers, Mikko Koivisto, Mathieu Liedloff, Sebastian Ordyniak, Stefan Szeider
2015	A	`conf`	Subset Sum in the Absence of Concentration. STACS Per Austrin, Petteri Kaski, Mikko Koivisto, Jesper Nederlof
2014	J	`jnl`	Fast monotone summation over disjoint sets. Inf. Process. Lett. Petteri Kaski, Mikko Koivisto, Janne H. Korhonen, Igor S. Sergeev
2014	—	`conf`	Learning Chordal Markov Networks by Dynamic Programming. NIPS Kustaa Kangas, Mikko Koivisto, Teppo Mikael Niinimäki
2014	B	`conf`	On the Number of Connected Sets in Bounded Degree Graphs. WG Kustaa Kangas, Petteri Kaski, Mikko Koivisto, Janne H. Korhonen
2014	A*	`conf`	Predicting the Hardness of Learning Bayesian Networks. AAAI Brandon M. Malone, Kustaa Kangas, Matti Järvisalo, Mikko Koivisto, Petri Myllymäki
2013	A*	`conf`	Annealed Importance Sampling for Structure Learning in Bayesian Networks. IJCAI Teppo Mikael Niinimäki, Mikko Koivisto
2013	J	`jnl`	Finding optimal Bayesian networks using precedence constraints. J. Mach. Learn. Res. Pekka Parviainen, Mikko Koivisto
2013	J	`jnl`	Separating OR, SUM, and XOR Circuits CoRR Magnus Find, Mika Göös, Matti Järvisalo, Petteri Kaski, Mikko Koivisto, Janne H. Korhonen
2013	J	`jnl`	Space--Time Tradeoffs for Subset Sum: An Improved Worst Case Algorithm CoRR Per Austrin, Petteri Kaski, Mikko Koivisto, Jussi Määttä
2013	—	`conf`	Space-Time Tradeoffs for Subset Sum: An Improved Worst Case Algorithm. ICALP (1) Per Austrin, Petteri Kaski, Mikko Koivisto, Jussi Määttä
2013	A	`conf`	Treedy: A Heuristic for Counting and Sampling Subsets. UAI Teppo Niinimaki, Mikko Koivisto
2013	J	`jnl`	Treedy: A Heuristic for Counting and Sampling Subsets. CoRR Teppo Niinimaki, Mikko Koivisto
2012	J	`jnl`	Advances in exact Bayesian structure discovery in Bayesian networks. CoRR Mikko Koivisto
2012	J	`jnl`	Exact Structure Discovery in Bayesian Networks with Less Space CoRR Pekka Parviainen, Mikko Koivisto
2012	J	`jnl`	Fast Monotone Summation over Disjoint Sets CoRR Petteri Kaski, Mikko Koivisto, Janne H. Korhonen
2012	B	`conf`	Fast Monotone Summation over Disjoint Sets. IPEC Petteri Kaski, Mikko Koivisto, Janne H. Korhonen
2012	A*	`conf`	Fast zeta transforms for lattices with few irreducibles. SODA Andreas Björklund, Mikko Koivisto, Thore Husfeldt, Jesper Nederlof, Petteri Kaski, Pekka Parviainen
2012	A	`conf`	Finding Efficient Circuits for Ensemble Computation. SAT Matti Järvisalo, Petteri Kaski, Mikko Koivisto, Janne H. Korhonen
2012	J	`jnl`	Homomorphic Hashing for Sparse Coefficient Extraction CoRR Petteri Kaski, Mikko Koivisto, Jesper Nederlof
2012	B	`conf`	Homomorphic Hashing for Sparse Coefficient Extraction. IPEC Petteri Kaski, Mikko Koivisto, Jesper Nederlof
2012	J	`jnl`	On Finding Optimal Polytrees CoRR Serge Gaspers, Mikko Koivisto, Mathieu Liedloff, Sebastian Ordyniak, Stefan Szeider
2012	A*	`conf`	On Finding Optimal Polytrees. AAAI Serge Gaspers, Mikko Koivisto, Mathieu Liedloff, Sebastian Ordyniak, Stefan Szeider
2012	J	`jnl`	Partial Order MCMC for Structure Discovery in Bayesian Networks CoRR Teppo Niinimaki, Pekka Parviainen, Mikko Koivisto
2012	J	`jnl`	The traveling salesman problem in bounded degree graphs. ACM Trans. Algorithms Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto
2011	—	`conf`	Ancestor Relations in the Presence of Unobserved Variables. ECML/PKDD (2) Pekka Parviainen, Mikko Koivisto
2011	J	`jnl`	Covering and packing in linear space. Inf. Process. Lett. Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto
2011	A	`conf`	Partial Order MCMC for Structure Discovery in Bayesian Networks. UAI Teppo Niinimaki, Pekka Parviainen, Mikko Koivisto
2010	A*	`conf`	A Space-Time Tradeoff for Permutation Problems. SODA Mikko Koivisto, Pekka Parviainen
2010	A	`conf`	Bayesian structure discovery in Bayesian networks with less space. AISTATS Pekka Parviainen, Mikko Koivisto
2010	—	`conf`	Covering and Packing in Linear Space. ICALP (1) Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto
2010	J	`jnl`	Evaluation of permanents in rings and semirings. Inf. Process. Lett. Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto
2010	J	`jnl`	Geodesic diameter of a polygonal domain in O(n^4 log n) time CoRR Mikko Koivisto, Valentin Polishchuk
2010	J	`jnl`	Narrow sieves for parameterized paths and packings CoRR Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto
2010	J	`jnl`	Trimmed Moebius Inversion and Graphs of Bounded Degree. Theory Comput. Syst. Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto
2009	J	`jnl`	Counting Paths and Packings in Halves CoRR Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto
2009	A	`conf`	Counting Paths and Packings in Halves. ESA Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto
2009	A	`conf`	Exact Structure Discovery in Bayesian Networks with Less Space. UAI Pekka Parviainen, Mikko Koivisto
2009	J	`jnl`	On evaluation of permanents CoRR Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto
2009	—	`conf`	Partitioning into Sets of Bounded Cardinality. IWPEC Mikko Koivisto
2009	J	`jnl`	Set Partitioning via Inclusion-Exclusion. SIAM J. Comput. Andreas Björklund, Thore Husfeldt, Mikko Koivisto
2008	—	`conf`	08431 Open Problems - Moderately Exponential Time Algorithms. Moderately Exponential Time Algorithms Fedor V. Fomin, Kazuo Iwama, Dieter Kratsch, Petteri Kaski, Mikko Koivisto, Lukasz Kowalik, Yoshio Okamoto, Johan M. M. van Rooij, Ryan Williams
2008	A*	`conf`	Computing the Tutte Polynomial in Vertex-Exponential Time. FOCS Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto
2008	C	`conf`	Fast Bayesian Haplotype Inference Via Context Tree Weighting. WABI Pasi Rastas, Jussi Kollin, Mikko Koivisto
2008	—	`conf`	The Travelling Salesman Problem in Bounded Degree Graphs. ICALP (1) Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto
2008	J	`jnl`	The fast intersection transform with applications to counting paths CoRR Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto
2008	J	`jnl`	Trimmed Moebius Inversion and Graphs of Bounded Degree CoRR Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto
2008	A	`conf`	Trimmed Moebius Inversion and Graphs of Bounded Degree. STACS Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto
2007	J	`jnl`	Computing the Tutte polynomial in vertex-exponential time CoRR Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto
2007	A*	`conf`	Fourier meets möbius: fast subset convolution. STOC Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto
2006	A	`conf`	Advances in Exact Bayesian Structure Discovery in Bayesian Networks. UAI Mikko Koivisto
2006	A*	`conf`	An O*(2^n ) Algorithm for Graph Coloring and Other Partitioning Problems via Inclusion--Exclusion. FOCS Mikko Koivisto
2006	—	`conf`	Bayesian Learning with Mixtures of Trees. ECML Jussi Kollin, Mikko Koivisto
2006	J	`jnl`	Fourier meets Möbius: fast subset convolution CoRR Andreas Björklund, Thore Husfeldt, Petteri Kaski, Mikko Koivisto
2006	J	`jnl`	Optimal 2-constraint satisfaction via sum-product algorithms. Inf. Process. Lett. Mikko Koivisto
2006	A*	`conf`	Parent Assignment Is Hard for the MDL, AIC, and NML Costs. COLT Mikko Koivisto
2005	C	`conf`	A Hidden Markov Technique for Haplotype Reconstruction. WABI Pasi Rastas, Mikko Koivisto, Heikki Mannila, Esko Ukkonen
2005	A*	`conf`	Computational aspects of Bayesian partition models. ICML Mikko Koivisto, Kismat Sood
2004	J	`jnl`	Exact Bayesian Structure Discovery in Bayesian Networks. J. Mach. Learn. Res. Mikko Koivisto, Kismat Sood
2004	B	`conf`	Hidden Markov Modelling Techniques for Haplotype Analysis. ALT Mikko Koivisto, Teemu Kivioja, Heikki Mannila, Pasi Rastas, Esko Ukkonen
2004	—	`conf`	Recombination Systems. Theory Is Forever Mikko Koivisto, Pasi Rastas, Esko Ukkonen
2003	Misc	`conf`	An MDL Method for Finding Haplotype Blocks and for Estimating the Strength of Haplotype Block Boundaries. Pacific Symposium on Biocomputing Mikko Koivisto, Markus Perola, T. Varilo, W. Hennah, J. Ekelund, Margus Lukk, L. Peltonen, Esko Ukkonen, Heikki Mannila