Teemu Roos

Publication Activity (10 Years)

Years Active: 2002-2024
Publications (10 Years): 31

Top Topics

Nearest Neighbor

Top Venues

Digit. Scholarsh. Humanit.

Publications

Nicolas Pope, Juho Kahila, Jari Laru, Henriikka Vartiainen, Teemu Roos, Matti Tedre
An Educational Tool for Learning about Social Media Tracking, Profiling, and Recommendation. CoRR (2024)
Daniel Holmberg, Manu Airaksinen, Viviana Marchi, Andrea Guzzetta, Anna Kivi, Leena Haataja, Sampsa Vanhatalo, Teemu Roos
Modeling 3D Infant Kinetics Using Adaptive Graph Convolutional Networks. CoRR (2024)
Aqsa Saeed Qureshi, Teemu Roos
Transfer Learning with Ensembles of Deep Neural Networks for Skin Cancer Detection in Imbalanced Data Sets. Neural Process. Lett. 55 (4) (2023)
Ioanna Bouri, Fanni Franssila, Markku Alho, Giulia Cozzani, Ivan Zaitsev, Minna Palmroth, Teemu Roos
Graph Representation of the Magnetic Field Topology in High-Fidelity Plasma Simulations for Machine Learning Applications. CoRR (2023)
Ville Hyvönen, Elias Jääsaari, Teemu Roos
A Multilabel Classification Framework for Approximate Nearest Neighbor Search. NeurIPS (2022)
Aqsa Saeed Qureshi, Teemu Roos
Transfer Learning with Ensembles of Deep Neural Networks for Skin Cancer Classification in Imbalanced Data Sets. CoRR (2021)
Jussi Määttä, Viacheslav Bazaliy, Jyri Kimari, Flyura Djurabekova, Kai Nordlund, Teemu Roos
Gradient-based training and pruning of radial basis function networks with an application in materials physics. Neural Networks 133 (2021)
Sotiris K. Tasoulis, Nicos G. Pavlidis, Teemu Roos
Nonlinear dimensionality reduction for clustering. Pattern Recognit. 107 (2020)
Jussi Määttä, Viacheslav Bazaliy, Jyri Kimari, Flyura Djurabekova, Kai Nordlund, Teemu Roos
Gradient-Based Training and Pruning of Radial Basis Function Networks with an Application in Materials Physics. CoRR (2020)
Peter Grünwald, Teemu Roos
Minimum Description Length Revisited. CoRR (2019)
Elias Jääsaari, Ville Hyvönen, Teemu Roos
Efficient Autotuning of Hyperparameters in Approximate Nearest Neighbor Search. PAKDD (2) (2019)
Ville Hyvönen, Elias Jääsaari, Teemu Roos
Supervised Learning Approach to Approximate Nearest Neighbor Search. CoRR (2019)
Elias Jääsaari, Ville Hyvönen, Teemu Roos
Efficient Autotuning of Hyperparameters in Approximate Nearest Neighbor Search. CoRR (2018)
Tuomas Heikkilä, Teemu Roos
Quantitative methods for the analysis of medieval calendars. Digit. Scholarsh. Humanit. 33 (4) (2018)
Tomi Silander, Janne Leppä-aho, Elias Jääsaari, Teemu Roos
Quotient Normalized Maximum Likelihood Criterion for Learning Bayesian Network Structures. AISTATS (2018)
Janne Leppä-aho, Santeri Räisänen, Xiao Yang, Teemu Roos
Learning Non-parametric Markov Networks with Mutual Information. PGM (2018)
Elias Jääsaari, Janne Leppä-aho, Tomi Silander, Teemu Roos
Minimax Optimal Bayes Mixtures for Memoryless Sources over Large Alphabets. ALT (2018)
Utsav Sheth, Sanghamitra Dutta, Malhar Chaudhari, Haewon Jeong, Yaoqing Yang, Jukka Kohonen, Teemu Roos, Pulkit Grover
An Application of Storage-Optimal MatDot Codes for Coded Matrix Multiplication: Fast k-Nearest Neighbors Estimation. IEEE BigData (2018)
Utsav Sheth, Sanghamitra Dutta, Malhar Chaudhari, Haewon Jeong, Yaoqing Yang, Jukka Kohonen, Teemu Roos, Pulkit Grover
An Application of Storage-Optimal MatDot Codes for Coded Matrix Multiplication: Fast k-Nearest Neighbors Estimation. CoRR (2018)
Janne Leppä-aho, Santeri Räisänen, Xiao Yang, Teemu Roos
Learning non-parametric Markov networks with mutual information. CoRR (2017)
Yuan Zou, Johan Pensar, Teemu Roos
Representing local structure in Bayesian networks by Boolean functions. Pattern Recognit. Lett. 95 (2017)
Janne Leppä-aho, Johan Pensar, Teemu Roos, Jukka Corander
Learning Gaussian graphical models with fractional marginal pseudo-likelihood. Int. J. Approx. Reason. 83 (2017)
Yuan Zou, Teemu Roos
On Model Selection, Bayesian Networks, and the Fisher Information Integral. New Gener. Comput. 35 (1) (2017)
Ville Hyvönen, Teemu Pitkänen, Sotiris K. Tasoulis, Elias Jaasaari, Risto Tuomainen, Liang Wang, Jukka Corander, Teemu Roos
Fast nearest neighbor search through sparse random projections and voting. IEEE BigData (2016)
Janne Leppä-aho, Johan Pensar, Teemu Roos, Jukka Corander
Learning Gaussian Graphical Models With Fractional Marginal Pseudo-likelihood. CoRR (2016)
Tuomas Heikkilä, Teemu Roos
Thematic Section on Studia Stemmatologica. Digit. Scholarsh. Humanit. 31 (3) (2016)
Yuan Zou, Teemu Roos
Sparse Logistic Regression with Logical Features. PAKDD (1) (2016)
Liang Wang, Sotiris K. Tasoulis, Teemu Roos, Jussi Kangasharju
Kvasir: Scalable Provision of Semantically Relevant Web Content on Big Data Framework. IEEE Trans. Big Data 2 (3) (2016)
Jamshid Tehrani, Quan Nguyen, Teemu Roos
Oral fairy tale or literary fake? Investigating the origins of Little Red Riding Hood using phylogenetic network analysis. Digit. Scholarsh. Humanit. 31 (3) (2016)
Jussi Määttä, Teemu Roos
Robust Sequential Prediction in Linear Regression with Student's t-distribution. ISAIM (2016)
Yang Zhao, Sotiris K. Tasoulis, Teemu Roos
Manifold Visualization via Short Walks. EuroVis (Short Papers) (2016)
Ville Hyvönen, Teemu Pitkänen, Sotiris K. Tasoulis, Liang Wang, Teemu Roos, Jukka Corander
Fast k-NN search. CoRR (2015)
Ralf Eggeling, Teemu Roos, Petri Myllymäki, Ivo Grosse
Inferring intra-motif dependencies of DNA binding sites from ChIP-seq data. BMC Bioinform. 16 (2015)
Liang Wang, Sotiris K. Tasoulis, Teemu Roos, Jussi Kangasharju
Kvasir: Seamless Integration of Latent Semantic Analysis-Based Content Provision into Web Browsing. WWW (Companion Volume) (2015)
Quan Nguyen, Teemu Roos
Likelihood-Based Inference of Phylogenetic Networks from Sequence Data by PhyloDAG. AlCoB (2015)
Yuan Zou, Teemu Roos
On Model Selection, Bayesian Networks, and the Fisher Information Integral. AMBN@JSAI-isAI (2015)
Kazuho Watanabe, Teemu Roos
Achievability of asymptotic minimax regret by horizon-dependent and horizon-independent strategies. J. Mach. Learn. Res. 16 (2015)
Michael Sherman, Gradeigh Clark, Yulong Yang, Shridatt Sugrim, Arttu Modig, Janne Lindqvist, Antti Oulasvirta, Teemu Roos
User-generated free-form gestures for authentication: security and memorability. MobiSys (2014)
Michael Sherman, Gradeigh Clark, Yulong Yang, Shridatt Sugrim, Arttu Modig, Janne Lindqvist, Antti Oulasvirta, Teemu Roos
Video: User-generated free-form gestures for authentication: security and memorability. MobiSys (2014)
Jussi Määttä, Samuli Siltanen, Teemu Roos
A fixed-point image denoising algorithm with automatic window selection. EUVIP (2014)
Michael Sherman, Gradeigh Clark, Yulong Yang, Shridatt Sugrim, Arttu Modig, Janne Lindqvist, Antti Oulasvirta, Teemu Roos
User-Generated Free-Form Gestures for Authentication: Security and Memorability. CoRR (2014)
Ralf Eggeling, Teemu Roos, Petri Myllymäki, Ivo Grosse
Robust learning of inhomogeneous PMMs. AISTATS (2014)
Andrew R. Barron, Teemu Roos, Kazuho Watanabe
Bayesian properties of normalized maximum likelihood and its fast computation. ISIT (2014)
Andrew R. Barron, Teemu Roos, Kazuho Watanabe
Bayesian Properties of Normalized Maximum Likelihood and its Fast Computation. CoRR (2014)
Sotiris K. Tasoulis, Lu Cheng, Niko Välimäki, Nicholas J. Croucher, Simon R. Harris, William P. Hanage, Teemu Roos, Jukka Corander
Random projection based clustering for population genomics. IEEE BigData (2014)
Antti Oulasvirta, Teemu Roos, Arttu Modig, Laura Leppänen
Information capacity of full-body movements. CHI (2013)
Kazuho Watanabe, Teemu Roos, Petri Myllymäki
Achievability of Asymptotic Minimax Regret in Online and Batch Prediction. ACML (2013)
Teemu Roos, Yuan Zou
Keep it simple stupid - On the effect of lower-order terms in BIC-like criteria. ITA (2013)
Teemu Roos, Petri Myllymäki, Tommi S. Jaakkola
Special Issue on the Fifth European Workshop on Probabilistic Graphical Models (PGM-2010). Int. J. Approx. Reason. 53 (9) (2012)
Teemu Roos, Yuan Zou
Analysis of Textual Variation by Latent Tree Structures. ICDM (2011)
Teemu Pulkkinen, Teemu Roos, Petri Myllymäki
Semi-supervised Learning for WLAN Positioning. ICANN (1) (2011)
Teemu Roos, Antti Oulasvirta
An Extended Framework for Measuring the Information Capacity of the Human Motor System CoRR (2011)
Alexandra M. Carvalho, Teemu Roos, Arlindo L. Oliveira, Petri Myllymäki
Discriminative Learning of Bayesian Networks via Factorized Conditional Log-Likelihood. J. Mach. Learn. Res. 12 (2011)
Po-Hsiang Lai, Teemu Roos, Joseph A. O'Sullivan
MDL hierarchical clustering for stemmatology. ISIT (2010)
Tomi Silander, Teemu Roos, Petri Myllymäki
Learning locally minimax optimal Bayesian networks. Int. J. Approx. Reason. 51 (5) (2010)
Jorma Rissanen, Teemu Roos, Petri Myllymäki
Model selection by sequentially normalized least squares. J. Multivar. Anal. 101 (4) (2010)
Tomi Silander, Teemu Roos, Petri Myllymäki
Locally Minimax Optimal Predictive Modeling with Bayesian Networks. AISTATS (2009)
Teemu Roos, Petri Myllymäki, Jorma Rissanen
MDL denoising revisited. IEEE Trans. Signal Process. 57 (9) (2009)
Teemu Roos, Tuomas Heikkilä
Evaluating methods for computer-assisted stemmatology using artificial benchmark data sets. Lit. Linguistic Comput. 24 (4) (2009)
Teemu Roos, Bin Yu
Sparse Markov source estimation via transformed Lasso. ITW (2009)
Teemu Roos
Monte Carlo estimation of minimax regret with an application to MDL model selection. ITW (2008)
Jorma Rissanen, Peter D. Grünwald, Jukka Heikkonen, Petri Myllymäki, Teemu Roos, Juho Rousu
Information Theoretic Methods for Bioinformatics. EURASIP J. Bioinform. Syst. Biol. 2007 (2007)
Teemu Roos, Tuomas Heikkilä, Petri Myllymäki
A Compression-Based Method for Stemmatic Analysis. ECAI (2006)
Teemu Roos, Petri Myllymäki, Jorma Rissanen
MDL Denoising Revisited CoRR (2006)
Teemu Roos, Peter Grünwald, Petri Myllymäki, Henry Tirri
Generalization to Unseen Cases. NIPS (2005)
Teemu Roos, Petri Myllymäki, Henry Tirri
On the Behavior of MDL Denoising. AISTATS (2005)
Teemu Roos, Hannes Wettig, Peter Grünwald, Petri Myllymäki, Henry Tirri
On Discriminative Bayesian Network Classifiers and Logistic Regression. Mach. Learn. 59 (3) (2005)
Teemu Roos, Peter Grünwald, Petri Myllymäki, Henry Tirri
Generalization to Unseen Cases. BNAIC (2005)
Petri Kontkanen, Petri Myllymäki, Teemu Roos, Henry Tirri, Kimmo Valtonen, Hannes Wettig
Topics in probabilistic location estimation in wireless networks. PIMRC (2004)
Hannes Wettig, Peter Grünwald, Teemu Roos, Petri Myllymäki, Henry Tirri
When Discriminative Learning of Bayesian Network Parameters Is Easy. IJCAI (2003)
Teemu Roos, Petri Myllymäki, Henry Tirri
A Statistical Modeling Approach to Location Estimation. IEEE Trans. Mob. Comput. 1 (1) (2002)
Teemu Roos, Petri Myllymäki, Henry Tirri, Pauli Misikangas, Juha Sievänen
A Probabilistic Approach to WLAN User Location Estimation. Int. J. Wirel. Inf. Networks 9 (3) (2002)