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- Teemu Roos, Petri Myllymäki, Henry Tirri, Pauli Misikangas, Juha Sievänen
- IJWIN
- 2002

We estimate the location of a WLAN user based on radio signal strength measurements performed by the user’s mobile terminal. In our approach the physical properties of the signal propagation are not… (More)

- Teemu Roos, Petri Myllymäki, Henry Tirri
- IEEE Trans. Mob. Comput.
- 2002

ÐSome location estimation methods, such as the GPS satellite navigation system, require nonstandard features either in the mobile terminal or the network. Solutions based on generic technologies not… (More)

- S. Karamanou, Eleftheria Vrontou, +5 authors A. Economou
- Molecular microbiology
- 1999

SecA, the dimeric ATPase subunit of bacterial protein translocase, catalyses translocation during ATP-driven membrane cycling at SecYEG. We now show that the SecA protomer comprises two structural… (More)

- Teemu Roos, Hannes Wettig, Peter Grünwald, Petri Myllymäki, Henry Tirri
- Machine Learning
- 2005

Discriminative learning of the parameters in the naive Bayes model is known to be equivalent to a logistic regression problem. Here we show that the same fact holds for much more general Bayesian… (More)

- Teemu Roos, Petri Myllymäki, Jorma Rissanen
- IEEE Transactions on Signal Processing
- 2009

We refine and extend an earlier minimum description length (MDL) denoising criterion for wavelet-based denoising. We start by showing that the denoising problem can be reformulated as a clustering… (More)

- Teemu Roos, Tuomas Heikkilä
- LLC
- 2009

Given a collection of imperfect copies of a textual document, the aim of stemmatology is to reconstruct the history of the text, indicating for each variant the sourcc tcxt from it was copied. We… (More)

- Jorma Rissanen, Teemu Roos
- 2007 Information Theory and Applications Workshop
- 2007

The NML (normalized maximum likelihood) universal model has certain minmax optimal properties but it has two shortcomings: the normalizing coefficient can be evaluated in a closed form only for… (More)

- Teemu Roos, Jorma Rissanen
- 2008

The important normalized maximum likelihood (NML) distribution is obtained via a normalization over all sequences of given length. It has two short-comings: the resulting model is usually not a… (More)

- Tomi Silander, Teemu Roos, Petri Myllymäki
- Int. J. Approx. Reasoning
- 2010

We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background knowledge is… (More)

- Teemu Roos
- 2008 IEEE Information Theory Workshop
- 2008

Minimum description length (MDL) model selection, in its modern NML formulation, involves a model complexity term which is equivalent to minimax/maximin regret. When the data are discrete-valued, the… (More)