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Publications information icon

Algorithms for learning parsimonious context trees

Peer-reviewed
Open access
DOI
10.1007/s10994-018-5770-9
Eggeling, Ralf; Grosse, Ivo; Koivisto, Mikko
Machine Learning2019Publications information icon

Focused multi-task learning in a Gaussian process framework

Peer-reviewed
DOI
10.1007/s10994-012-5302-y
Leen, Gayle; Peltonen, Jaakko; Kaski, Samuel
Machine learning2012Publications information icon

Sparse and low-rank matrix regularization for learning time-varying Markov networks

Peer-reviewed
Open access
DOI
10.1007/s10994-016-5568-6
Hirayama, Jun-ichiro; Hyvarinen, Aapo; Ishii, Shin
Machine Learning2016Publications information icon

Empirical Hardness of Finding Optimal Bayesian Network Structures: Algorithm Selection and Runtime Prediction

Peer-reviewed
Open access
DOI
10.1007/s10994-017-5680-2
Malone, Brandon; Kangas, Kustaa; Järvisalo, Matti; Koivisto, Mikko; Myllymäki, Petri
Machine Learning2018Publications information icon

Recurrent segmentation meets block models in temporal networks

Peer-reviewed
Open access
DOI
10.1007/s10994-023-06507-6
Wickrama Arachchi, Wickrama Arachchige Chamalee Nisansala; Tatti, Nikolaj
Machine Learning2024Publications information icon

Jaccard-constrained dense subgraph discovery

Peer-reviewed
Open access
DOI
10.1007/s10994-024-06595-y
Wickrama Arachchi, Wickrama Arachchige Chamalee Nisansala; Tatti, Nikolaj
Machine Learning2024Publications information icon

Dense subgraphs induced by edge labels

Peer-reviewed
Open access
DOI
10.1007/s10994-023-06377-y
Kumpulainen, Iiro; Tatti, Nikolaj
Machine Learning2023Publications information icon

SLISEMAP: supervised dimensionality reduction through local explanations

Peer-reviewed
Open access
DOI
10.1007/s10994-022-06261-1
Björklund, Anton; Mäkelä, Jarmo; Puolamäki, Kai
Machine Learning2023Publications information icon

Maintaining AUC and H-measure over time

Peer-reviewed
Open access
DOI
10.1007/s10994-021-06084-6
Tatti, Nikolaj
Machine Learning2022Publications information icon

A deep neural network to search for new long-lived particles decaying to jets

Peer-reviewed
Open access
DOI
10.1088/2632-2153/ab9023
The CMS collaboration; Sirunyan, A. M.; Tumasyan, A.; Eerola, P.; Forthomme, Laurent; Kirschenmann, ...
Machine Learning2020

Algorithms for learning parsimonious context trees

Peer-reviewed
Open access
DOI
10.1007/s10994-018-5770-9
2019

Focused multi-task learning in a Gaussian process framework

Peer-reviewed
DOI
10.1007/s10994-012-5302-y
2012

Sparse and low-rank matrix regularization for learning time-varying Markov networks

Peer-reviewed
Open access
DOI
10.1007/s10994-016-5568-6
2016

Empirical Hardness of Finding Optimal Bayesian Network Structures: Algorithm Selection and Runtime Prediction

Peer-reviewed
Open access
DOI
10.1007/s10994-017-5680-2
2018

Recurrent segmentation meets block models in temporal networks

Peer-reviewed
Open access
DOI
10.1007/s10994-023-06507-6
2024

Jaccard-constrained dense subgraph discovery

Peer-reviewed
Open access
DOI
10.1007/s10994-024-06595-y
2024

Dense subgraphs induced by edge labels

Peer-reviewed
Open access
DOI
10.1007/s10994-023-06377-y
2023

SLISEMAP: supervised dimensionality reduction through local explanations

Peer-reviewed
Open access
DOI
10.1007/s10994-022-06261-1
2023

Maintaining AUC and H-measure over time

Peer-reviewed
Open access
DOI
10.1007/s10994-021-06084-6
2022

A deep neural network to search for new long-lived particles decaying to jets

Peer-reviewed
Open access
DOI
10.1088/2632-2153/ab9023
2020