A Probabilistic Approach to WLAN User Location Estimation. - Teemu Roos; Petri Myllymäki; Henry Tirri; Pauli Misikangas; Juha Sievänen (Int. J. Wirel. Inf. Networks, 2002)

A Statistical Modeling Approach to Location Estimation. - Teemu Roos; Petri Myllymäki; Henry Tirri (IEEE Trans. Mob. Comput., 2002)

When Discriminative Learning of Bayesian Network Parameters Is Easy. - Hannes Wettig; Peter Grünwald; Teemu Roos; Petri Myllymäki; Henry Tirri (IJCAI, 2003)

Topics in probabilistic location estimation in wireless networks. - Petri Kontkanen; Petri Myllymäki; Teemu Roos; Henry Tirri; Kimmo Valtonen; Hannes Wettig (PIMRC, 2004)

On the Behavior of MDL Denoising. - Teemu Roos; Petri Myllymäki; Henry Tirri (AISTATS, 2005)

Generalization to Unseen Cases. - Teemu Roos; Peter Grünwald; Petri Myllymäki; Henry Tirri (NIPS, 2005)

On Discriminative Bayesian Network Classifiers and Logistic Regression. - Teemu Roos; Hannes Wettig; Peter Grünwald; Petri Myllymäki; Henry Tirri (Mach. Learn., 2005)

A Compression-Based Method for Stemmatic Analysis. - Teemu Roos; Tuomas Heikkilä; Petri Myllymäki (ECAI, 2006)

Information Theoretic Methods for Bioinformatics. - Jorma Rissanen; Peter D. Grünwald; Jukka Heikkonen; Petri Myllymäki; Teemu Roos; Juho Rousu (EURASIP J. Bioinform. Syst. Biol., 2007)

Monte Carlo estimation of minimax regret with an application to MDL model selection. - Teemu Roos (ITW, 2008)

Sparse Markov source estimation via transformed Lasso. - Teemu Roos; Bin Yu (ITW, 2009)

Locally Minimax Optimal Predictive Modeling with Bayesian Networks. - Tomi Silander; Teemu Roos; Petri Myllymäki (AISTATS, 2009)

Evaluating methods for computer-assisted stemmatology using artificial benchmark data sets. - Teemu Roos; Tuomas Heikkilä (Lit. Linguistic Comput., 2009)

MDL denoising revisited. - Teemu Roos; Petri Myllymäki; Jorma Rissanen (IEEE Trans. Signal Process., 2009)

MDL hierarchical clustering for stemmatology. - Po-Hsiang Lai; Teemu Roos; Joseph A. O'Sullivan (ISIT, 2010)

Learning locally minimax optimal Bayesian networks. - Tomi Silander; Teemu Roos; Petri Myllymäki (Int. J. Approx. Reason., 2010)

Model selection by sequentially normalized least squares. - Jorma Rissanen; Teemu Roos; Petri Myllymäki (J. Multivar. Anal., 2010)

Semi-supervised Learning for WLAN Positioning. - Teemu Pulkkinen; Teemu Roos; Petri Myllymäki (ICANN (1), 2011)

Analysis of Textual Variation by Latent Tree Structures. - Teemu Roos; Yuan Zou (ICDM, 2011)

An Extended Framework for Measuring the Information Capacity of the Human Motor System - Teemu Roos; Antti Oulasvirta (CoRR, 2011)

Discriminative Learning of Bayesian Networks via Factorized Conditional Log-Likelihood. - Alexandra M. Carvalho; Teemu Roos; Arlindo L. Oliveira; Petri Myllymäki (J. Mach. Learn. Res., 2011)

Special Issue on the Fifth European Workshop on Probabilistic Graphical Models (PGM-2010). - Teemu Roos; Petri Myllymäki; Tommi S. Jaakkola (Int. J. Approx. Reason., 2012)

Achievability of Asymptotic Minimax Regret in Online and Batch Prediction. - Kazuho Watanabe; Teemu Roos; Petri Myllymäki (ACML, 2013)

Information capacity of full-body movements. - Antti Oulasvirta; Teemu Roos; Arttu Modig; Laura Leppänen (CHI, 2013)

Keep it simple stupid - On the effect of lower-order terms in BIC-like criteria. - Teemu Roos; Yuan Zou (ITA, 2013)

Robust learning of inhomogeneous PMMs. - Ralf Eggeling; Teemu Roos; Petri Myllymäki; Ivo Grosse (AISTATS, 2014)

Random projection based clustering for population genomics. - Sotiris K. Tasoulis; Lu Cheng 004; Niko Välimäki; Nicholas J. Croucher; Simon R. Harris; William P. Hanage; Teemu Roos; Jukka Corander (IEEE BigData, 2014)

A fixed-point image denoising algorithm with automatic window selection. - Jussi Määttä; Samuli Siltanen; Teemu Roos (EUVIP, 2014)

Bayesian properties of normalized maximum likelihood and its fast computation. - Andrew R. Barron; Teemu Roos; Kazuho Watanabe (ISIT, 2014)

User-generated free-form gestures for authentication: security and memorability. - Michael Sherman; Gradeigh Clark; Yulong Yang 001; Shridatt Sugrim; Arttu Modig; Janne Lindqvist; Antti Oulasvirta; Teemu Roos (MobiSys, 2014)

Video: User-generated free-form gestures for authentication: security and memorability. - Michael Sherman; Gradeigh Clark; Yulong Yang 001; Shridatt Sugrim; Arttu Modig; Janne Lindqvist; Antti Oulasvirta; Teemu Roos (MobiSys, 2014)

Likelihood-Based Inference of Phylogenetic Networks from Sequence Data by PhyloDAG. - Quan Nguyen; Teemu Roos (AlCoB, 2015)

Kvasir: Seamless Integration of Latent Semantic Analysis-Based Content Provision into Web Browsing. - Liang Wang 009; Sotiris K. Tasoulis; Teemu Roos; Jussi Kangasharju (WWW (Companion Volume), 2015)

Inferring intra-motif dependencies of DNA binding sites from ChIP-seq data. - Ralf Eggeling; Teemu Roos; Petri Myllymäki; Ivo Grosse (BMC Bioinform., 2015)

Fast k-NN search. - Ville Hyvönen; Teemu Pitkänen; Sotiris K. Tasoulis; Liang Wang 009; Teemu Roos; Jukka Corander (CoRR, 2015)

Achievability of asymptotic minimax regret by horizon-dependent and horizon-independent strategies. - Kazuho Watanabe; Teemu Roos (J. Mach. Learn. Res., 2015)

Fast nearest neighbor search through sparse random projections and voting. - Ville Hyvönen; Teemu Pitkänen; Sotiris K. Tasoulis; Elias Jaasaari; Risto Tuomainen; Liang Wang 009; Jukka Corander; Teemu Roos (IEEE BigData, 2016)

Robust Sequential Prediction in Linear Regression with Student's t-distribution. - Jussi Määttä; Teemu Roos (ISAIM, 2016)

Sparse Logistic Regression with Logical Features. - Yuan Zou; Teemu Roos (PAKDD (1), 2016)

Manifold Visualization via Short Walks. - Yang Zhao; Sotiris K. Tasoulis; Teemu Roos (EuroVis (Short Papers), 2016)

Thematic Section on Studia Stemmatologica. - Tuomas Heikkilä; Teemu Roos (Digit. Scholarsh. Humanit., 2016)

Oral fairy tale or literary fake? Investigating the origins of Little Red Riding Hood using phylogenetic network analysis. - Jamshid Tehrani; Quan Nguyen; Teemu Roos (Digit. Scholarsh. Humanit., 2016)

Kvasir: Scalable Provision of Semantically Relevant Web Content on Big Data Framework. - Liang Wang 009; Sotiris K. Tasoulis; Teemu Roos; Jussi Kangasharju (IEEE Trans. Big Data, 2016)

Learning Gaussian graphical models with fractional marginal pseudo-likelihood. - Janne Leppä-aho; Johan Pensar; Teemu Roos; Jukka Corander (Int. J. Approx. Reason., 2017)

On Model Selection, Bayesian Networks, and the Fisher Information Integral. - Yuan Zou; Teemu Roos (New Gener. Comput., 2017)

Representing local structure in Bayesian networks by Boolean functions. - Yuan Zou; Johan Pensar; Teemu Roos (Pattern Recognit. Lett., 2017)

Minimum Description Length Principle. - Teemu Roos (Encyclopedia of Machine Learning and Data Mining, 2017)

Quotient Normalized Maximum Likelihood Criterion for Learning Bayesian Network Structures. - Tomi Silander; Janne Leppä-aho; Elias Jääsaari; Teemu Roos (AISTATS, 2018)

Minimax Optimal Bayes Mixtures for Memoryless Sources over Large Alphabets. - Elias Jääsaari; Janne Leppä-aho; Tomi Silander; Teemu Roos (ALT, 2018)

An Application of Storage-Optimal MatDot Codes for Coded Matrix Multiplication: Fast k-Nearest Neighbors Estimation. - Utsav Sheth; Sanghamitra Dutta; Malhar Chaudhari; Haewon Jeong; Yaoqing Yang; Jukka Kohonen; Teemu Roos; Pulkit Grover (IEEE BigData, 2018)

Learning Non-parametric Markov Networks with Mutual Information. - Janne Leppä-aho; Santeri Räisänen; Xiao Yang; Teemu Roos (PGM, 2018)

Quantitative methods for the analysis of medieval calendars. - Tuomas Heikkilä; Teemu Roos (Digit. Scholarsh. Humanit., 2018)

Efficient Autotuning of Hyperparameters in Approximate Nearest Neighbor Search. - Elias Jääsaari; Ville Hyvönen; Teemu Roos (PAKDD (2), 2019)

Minimum Description Length Revisited. - Peter Grünwald; Teemu Roos (CoRR, 2019)

Supervised Learning Approach to Approximate Nearest Neighbor Search. - Ville Hyvönen; Elias Jääsaari; Teemu Roos (CoRR, 2019)

Nonlinear dimensionality reduction for clustering. - Sotiris K. Tasoulis; Nicos G. Pavlidis; Teemu Roos (Pattern Recognit., 2020)

Transfer Learning with Ensembles of Deep Neural Networks for Skin Cancer Classification in Imbalanced Data Sets. - Aqsa Saeed Qureshi; Teemu Roos (CoRR, 2021)

Gradient-based training and pruning of radial basis function networks with an application in materials physics. - Jussi Määttä; Viacheslav Bazaliy; Jyri Kimari; Flyura Djurabekova; Kai Nordlund; Teemu Roos (Neural Networks, 2021)

Graph Representation of the Magnetic Field Topology in High-Fidelity Plasma Simulations for Machine Learning Applications. - Ioanna Bouri; Fanni Franssila; Markku Alho; Giulia Cozzani; Ivan Zaitsev; Minna Palmroth; Teemu Roos (CoRR, 2023)

Transfer Learning with Ensembles of Deep Neural Networks for Skin Cancer Detection in Imbalanced Data Sets. - Aqsa Saeed Qureshi; Teemu Roos (Neural Process. Lett., 2023)

An Educational Tool for Learning about Social Media Tracking, Profiling, and Recommendation. - Nicolas Pope; Juho Kahila; Jari Laru; Henriikka Vartiainen; Teemu Roos; Matti Tedre (ICALT, 2024)

LoRANN: Low-Rank Matrix Factorization for Approximate Nearest Neighbor Search. - Elias Jääsaari; Ville Hyvönen; Teemu Roos (NeurIPS, 2024)

Modeling 3D Infant Kinetics Using Adaptive Graph Convolutional Networks. - Daniel Holmberg; Manu Airaksinen; Viviana Marchi; Andrea Guzzetta; Anna Kivi; Leena M. Haataja; Sampsa Vanhatalo; Teemu Roos (CoRR, 2024)

Regional Ocean Forecasting with Hierarchical Graph Neural Networks. - Daniel Holmberg; Emanuela Clementi; Teemu Roos (CoRR, 2024)

A Multilabel Classification Framework for Approximate Nearest Neighbor Search. - Ville Hyvönen; Elias Jääsaari; Teemu Roos (J. Mach. Learn. Res., 2024)

An XAI Social Media Platform for Teaching K-12 Students AI-Driven Profiling, Clustering, and Engagement-Based Recommending. - Nicolas Pope; Juho Kahila; Henriikka Vartiainen; Mohammed Saqr; Sonsoles López-Pernas; Teemu Roos; Jari Laru; Matti Tedre (AAAI, 2025)

VIBE: Vector Index Benchmark for Embeddings. - Elias Jääsaari; Ville Hyvönen; Matteo Ceccarello; Teemu Roos; Martin Aumüller 001 (CoRR, 2025)