Mikko Koivisto

Orcid: 0000-0001-9662-3605

Affiliations:
  • University of Helsinki, Finland


According to our database1, Mikko Koivisto authored at least 82 papers between 2003 and 2024.

Collaborative distances:
  • Dijkstra number2 of three.
  • Erdős number3 of two.

Timeline

2005
2010
2015
2020
0
1
2
3
4
5
6
7
8
9
1
1
2
2
3
1
3
1
1
1
1
1
3
2
1
1
1
1
3
1
1
5
3
5
2
3
3
2
3
3
2
2
3
4
1
4
2
2
1

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Approximate Counting of Linear Extensions in Practice.
J. Artif. Intell. Res., 2024

Estimating the Permanent by Nesting Importance Sampling.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
Quantum Speedups for Bayesian Network Structure Learning.
CoRR, 2023

On inference and learning with probabilistic generating circuits.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

Revisiting Bayesian network learning with small vertex cover.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

A Faster Practical Approximation Scheme for the Permanent.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Trustworthy Monte Carlo.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
Approximating the Permanent with Deep Rejection Sampling.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
NP-completeness results for partitioning a graph into total dominating sets.
Theor. Comput. Sci., 2020

A Faster Tree-Decomposition Based Algorithm for Counting Linear Extensions.
Algorithmica, 2020

Layering-MCMC for Structure Learning in Bayesian Networks.
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Fast Multi-Subset Transform and Weighted Sums over Acyclic Digraphs.
Proceedings of the 17th Scandinavian Symposium and Workshops on Algorithm Theory, 2020

Towards Scalable Bayesian Learning of Causal DAGs.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

A Bayesian Approach for Estimating Causal Effects from Observational Data.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Error-Correcting and Verifiable Parallel Inference in Graphical Models.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Algorithms for learning parsimonious context trees.
Mach. Learn., 2019

Learning Bayesian networks with local structure, mixed variables, and exact algorithms.
Int. J. Approx. Reason., 2019

Exact Sampling of Directed Acyclic Graphs from Modular Distributions.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

On Structure Priors for Learning Bayesian Networks.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Counting and Sampling Markov Equivalent Directed Acyclic Graphs.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Sharper Upper Bounds for Unbalanced Uniquely Decodable Code Pairs.
IEEE Trans. Inf. Theory, 2018

Empirical hardness of finding optimal Bayesian network structures: algorithm selection and runtime prediction.
Mach. Learn., 2018

On the Number of Connected Sets in Bounded Degree Graphs.
Electron. J. Comb., 2018

Finding Optimal Bayesian Networks with Local Structure.
Proceedings of the International Conference on Probabilistic Graphical Models, 2018

Counting Connected Subgraphs with Maximum-Degree-Aware Sieving.
Proceedings of the 29th International Symposium on Algorithms and Computation, 2018

A Scalable Scheme for Counting Linear Extensions.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Intersection-Validation: A Method for Evaluating Structure Learning without Ground Truth.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Counting Linear Extensions in Practice: MCMC Versus Exponential Monte Carlo.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Narrow sieves for parameterized paths and packings.
J. Comput. Syst. Sci., 2017

AS-ASL: Algorithm Selection with Auto-sklearn.
Proceedings of the Open Algorithm Selection Challenge 2017, 2017

The Mixing of Markov Chains on Linear Extensions in Practice.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

2016
Fast Zeta Transforms for Lattices with Few Irreducibles.
ACM Trans. Algorithms, 2016

Structure Discovery in Bayesian Networks by Sampling Partial Orders.
J. Mach. Learn. Res., 2016

Separating OR, SUM, and XOR circuits.
J. Comput. Syst. Sci., 2016

Pruning Rules for Learning Parsimonious Context Trees.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Dense Subset Sum May Be the Hardest.
Proceedings of the 33rd Symposium on Theoretical Aspects of Computer Science, 2016

Counting Linear Extensions of Sparse Posets.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

2015
On finding optimal polytrees.
Theor. Comput. Sci., 2015

Averaging of Decomposable Graphs by Dynamic Programming and Sampling.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Subset Sum in the Absence of Concentration.
Proceedings of the 32nd International Symposium on Theoretical Aspects of Computer Science, 2015

Dealing with small data: On the generalization of context trees.
Proceedings of the 32nd International Conference on Machine Learning, 2015

2014
Fast monotone summation over disjoint sets.
Inf. Process. Lett., 2014

Learning Chordal Markov Networks by Dynamic Programming.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Predicting the Hardness of Learning Bayesian Networks.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013
Finding optimal Bayesian networks using precedence constraints.
J. Mach. Learn. Res., 2013

Treedy: A Heuristic for Counting and Sampling Subsets.
Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

Annealed Importance Sampling for Structure Learning in Bayesian Networks.
Proceedings of the IJCAI 2013, 2013

Space-Time Tradeoffs for Subset Sum: An Improved Worst Case Algorithm.
Proceedings of the Automata, Languages, and Programming - 40th International Colloquium, 2013

2012
The traveling salesman problem in bounded degree graphs.
ACM Trans. Algorithms, 2012

Finding Efficient Circuits for Ensemble Computation.
Proceedings of the Theory and Applications of Satisfiability Testing - SAT 2012, 2012

Homomorphic Hashing for Sparse Coefficient Extraction.
Proceedings of the Parameterized and Exact Computation - 7th International Symposium, 2012

Fast Monotone Summation over Disjoint Sets.
Proceedings of the Parameterized and Exact Computation - 7th International Symposium, 2012

2011
Covering and packing in linear space.
Inf. Process. Lett., 2011

Partial Order MCMC for Structure Discovery in Bayesian Networks.
Proceedings of the UAI 2011, 2011

Ancestor Relations in the Presence of Unobserved Variables.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

2010
Trimmed Moebius Inversion and Graphs of Bounded Degree.
Theory Comput. Syst., 2010

Bayesian structure discovery in Bayesian networks with less space.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Evaluation of permanents in rings and semirings.
Inf. Process. Lett., 2010

Geodesic diameter of a polygonal domain in O(n^4 log n) time
CoRR, 2010

A Space-Time Tradeoff for Permutation Problems.
Proceedings of the Twenty-First Annual ACM-SIAM Symposium on Discrete Algorithms, 2010

2009
Set Partitioning via Inclusion-Exclusion.
SIAM J. Comput., 2009

On evaluation of permanents
CoRR, 2009

Exact Structure Discovery in Bayesian Networks with Less Space.
Proceedings of the UAI 2009, 2009

Partitioning into Sets of Bounded Cardinality.
Proceedings of the Parameterized and Exact Computation, 4th International Workshop, 2009

Counting Paths and Packings in Halves.
Proceedings of the Algorithms, 2009

2008
The fast intersection transform with applications to counting paths
CoRR, 2008

Fast Bayesian Haplotype Inference Via Context Tree Weighting.
Proceedings of the Algorithms in Bioinformatics, 8th International Workshop, 2008

The Travelling Salesman Problem in Bounded Degree Graphs.
Proceedings of the Automata, Languages and Programming, 35th International Colloquium, 2008

Computing the Tutte Polynomial in Vertex-Exponential Time.
Proceedings of the 49th Annual IEEE Symposium on Foundations of Computer Science, 2008

08431 Open Problems - Moderately Exponential Time Algorithms.
Proceedings of the Moderately Exponential Time Algorithms, 19.10. - 24.10.2008, 2008

2007
Fourier meets möbius: fast subset convolution.
Proceedings of the 39th Annual ACM Symposium on Theory of Computing, 2007

2006
Optimal 2-constraint satisfaction via sum-product algorithms.
Inf. Process. Lett., 2006

Advances in Exact Bayesian Structure Discovery in Bayesian Networks.
Proceedings of the UAI '06, 2006

An O*(2^n ) Algorithm for Graph Coloring and Other Partitioning Problems via Inclusion--Exclusion.
Proceedings of the 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS 2006), 2006

Bayesian Learning with Mixtures of Trees.
Proceedings of the Machine Learning: ECML 2006, 2006

Parent Assignment Is Hard for the MDL, AIC, and NML Costs.
Proceedings of the Learning Theory, 19th Annual Conference on Learning Theory, 2006

2005
A Hidden Markov Technique for Haplotype Reconstruction.
Proceedings of the Algorithms in Bioinformatics, 5th International Workshop, 2005

Computational aspects of Bayesian partition models.
Proceedings of the Machine Learning, 2005

2004
Exact Bayesian Structure Discovery in Bayesian Networks.
J. Mach. Learn. Res., 2004

Recombination Systems.
Proceedings of the Theory Is Forever, 2004

Hidden Markov Modelling Techniques for Haplotype Analysis.
Proceedings of the Algorithmic Learning Theory, 15th International Conference, 2004

2003
An MDL Method for Finding Haplotype Blocks and for Estimating the Strength of Haplotype Block Boundaries.
Proceedings of the 8th Pacific Symposium on Biocomputing, 2003


  Loading...