Kustaa Kangas

According to our database, Kustaa Kangas authored at least 12 papers between 2014 and 2020.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2020

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

Kustaa Kangas, Mikko Koivisto, Sami Salonen

Algorithmica, 2020

2019

Counting Linear Extensions: Parameterizations by Treewidth.

Eduard Eiben, Robert Ganian, Kustaa Kangas, Sebastian Ordyniak

Algorithmica, 2019

2018

Empirical hardness of finding optimal Bayesian network structures: algorithm selection and runtime prediction.

Brandon M. Malone, Kustaa Kangas, Matti Järvisalo, Mikko Koivisto, Petri Myllymäki

Mach. Learn., 2018

On the Number of Connected Sets in Bounded Degree Graphs.

Kustaa Kangas, Petteri Kaski, Janne H. Korhonen, Mikko Koivisto

Electron. J. Comb., 2018

A Scalable Scheme for Counting Linear Extensions.

Topi Talvitie, Kustaa Kangas, Teppo Mikael Niinimäki, Mikko Koivisto

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Counting Linear Extensions in Practice: MCMC Versus Exponential Monte Carlo.

Topi Talvitie, Kustaa Kangas, Teppo Mikael Niinimäki, Mikko Koivisto

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

AS-ASL: Algorithm Selection with Auto-sklearn.

Brandon M. Malone, Kustaa Kangas, Matti Järvisalo, Mikko Koivisto, Petri Myllymäki

Proceedings of the Open Algorithm Selection Challenge 2017, 2017

2016

Combinatorial Algorithms with Applications in Learning Graphical Models.

Kustaa Kangas

PhD thesis, 2016

Counting Linear Extensions of Sparse Posets.

Kustaa Kangas, Teemu Hankala, Teppo Mikael Niinimäki, Mikko Koivisto

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

2015

Averaging of Decomposable Graphs by Dynamic Programming and Sampling.

Kustaa Kangas, Teppo Mikael Niinimäki, Mikko Koivisto

Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

2014

Learning Chordal Markov Networks by Dynamic Programming.

Kustaa Kangas, Mikko Koivisto, Teppo Mikael Niinimäki

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.

Brandon M. Malone, Kustaa Kangas, Matti Järvisalo, Mikko Koivisto, Petri Myllymäki

Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014