Lasse Holmström

20 papers B 1C 2Journal 13Unranked 4
YearRankTypeTitle / Venue / Authors
2018 J jnl
A scale space approach for exploring structure in spherical data.
Comput. Stat. Data Anal.
Ville Vuollo, Lasse Holmström
2017 J jnl
Estimation of level set trees using adaptive partitions.
Comput. Stat.
Lasse Holmström, Kyösti Karttunen, Jussi Klemelä
2017 J jnl
Modeling probability density through ultraspherical polynomial transformations.
Commun. Stat. Simul. Comput.
Terhi Mäkinen, Lasse Holmström
2017 J jnl
Multivariate posterior singular spectrum analysis.
Stat. Methods Appl.
Ilkka Launonen, Lasse Holmström
2017 J jnl
Scale space multiresolution correlation analysis for time series data.
Comput. Stat.
Leena Pasanen, Lasse Holmström
2014 — conf
Level Set Trees with Enhanced Marginal Density Visualization.
IVAPP
Kyösti Karttunen, Lasse Holmström, Jussi Klemelä
2013 C conf
Bayesian scale space analysis of images.
ISPA
Leena Pasanen, Lasse Holmström
2013 J jnl
Posterior singular spectrum analysis.
Stat. Anal. Data Min.
Lasse Holmström, Ilkka Launonen
2012 J jnl
Bayesian Scale Space Analysis of Differences in Images.
Technometrics
Lasse Holmström, Leena Pasanen
2011 J jnl
Scale space multiresolution analysis of random signals.
Comput. Stat. Data Anal.
Lasse Holmström, Leena Pasanen, Reinhard Furrer, Stephan R. Sain
2004 J jnl
A semiparametric density estimation approach to pattern classification.
Pattern Recognit.
Fabian Hoti, Lasse Holmström
2004 — conf
Application of Semiparametric Density Estimation to Classification.
ICPR (3)
Lasse Holmström, Fabian Hoti
2002 J jnl
Making inferences about past environmental change using smoothing in multiple time scales.
Comput. Stat. Data Anal.
Lasse Holmström, Panu Erästö
1997 J jnl
Neural and statistical classifiers-taxonomy and two case studies.
IEEE Trans. Neural Networks
Lasse Holmström, Petri Koistinen, Jorma Laaksonen, Erkki Oja
1996 C conf
Complexity Reduction in Probabilistic Neural Networks.
ICANN
Ari Hämäläinen, Lasse Holmström
1996 B conf
Neural network and statistical perspectives of classification.
ICPR
Lasse Holmström, Petri Koistinen, Jorma Laaksonen, Erkki Oja
1993 — conf
The self-organizing reduced kernel density estimator.
ICNN
Lasse Holmström, Ari Hämäläinen
1992 J jnl
Using additive noise in back-propagation training.
IEEE Trans. Neural Networks
Lasse Holmström, Petri Koistinen
1991 — conf
Kernel Regression and Backpropagation Training With Noise.
NIPS
Petri Koistinen, Lasse Holmström
1987 J jnl
Piecewise quadric blending of implicitly defined surfaces.
Comput. Aided Geom. Des.
Lasse Holmström