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ORCIDTeemu Roos
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- affiliation: University of Helsinki, FI
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2020 – today
- 2024
[j23]Ville Hyvönen, Elias Jääsaari, Teemu Roos:
A Multilabel Classification Framework for Approximate Nearest Neighbor Search. J. Mach. Learn. Res. 25: 46:1-46:51 (2024)- [c35]Nicolas Pope, Juho Kahila, Jari Laru, Henriikka Vartiainen, Teemu Roos, Matti Tedre:
An Educational Tool for Learning about Social Media Tracking, Profiling, and Recommendation. ICALT 2024: 110-112 - [i19]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 abs/2402.01813 (2024) - [i18]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 abs/2402.14400 (2024) - [i17]Tomi Silander, Janne Leppä-aho, Elias Jääsaari, Teemu Roos:
Quotient Normalized Maximum Likelihood Criterion for Learning Bayesian Network Structures. CoRR abs/2408.14935 (2024) - [i16]Daniel Holmberg, Emanuela Clementi, Teemu Roos:
Regional Ocean Forecasting with Hierarchical Graph Neural Networks. CoRR abs/2410.11807 (2024) - [i15]Elias Jääsaari, Ville Hyvönen, Teemu Roos:
LoRANN: Low-Rank Matrix Factorization for Approximate Nearest Neighbor Search. CoRR abs/2410.18926 (2024) - 2023
- [j22]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): 4461-4479 (2023) - [i14]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 abs/2307.09469 (2023) - 2022
- [c34]Ville Hyvönen, Elias Jääsaari, Teemu Roos:
A Multilabel Classification Framework for Approximate Nearest Neighbor Search. NeurIPS 2022 - 2021
- [j21]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: 123-131 (2021) - [i13]Aqsa Saeed Qureshi, Teemu Roos:
Transfer Learning with Ensembles of Deep Neural Networks for Skin Cancer Classification in Imbalanced Data Sets. CoRR abs/2103.12068 (2021) - 2020
- [j20]Sotiris K. Tasoulis, Nicos G. Pavlidis, Teemu Roos:
Nonlinear dimensionality reduction for clustering. Pattern Recognit. 107: 107508 (2020) - [i12]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 abs/2004.02569 (2020)
2010 – 2019
- 2019
- [c33]Elias Jääsaari, Ville Hyvönen, Teemu Roos:
Efficient Autotuning of Hyperparameters in Approximate Nearest Neighbor Search. PAKDD (2) 2019: 590-602 - [i11]Peter Grünwald, Teemu Roos:
Minimum Description Length Revisited. CoRR abs/1908.08484 (2019) - [i10]Ville Hyvönen, Elias Jääsaari, Teemu Roos:
Supervised Learning Approach to Approximate Nearest Neighbor Search. CoRR abs/1910.08322 (2019) - 2018
- [j19]Tuomas Heikkilä, Teemu Roos:
Quantitative methods for the analysis of medieval calendars. Digit. Scholarsh. Humanit. 33(4): 766-787 (2018) - [c32]Tomi Silander, Janne Leppä-aho, Elias Jääsaari, Teemu Roos:
Quotient Normalized Maximum Likelihood Criterion for Learning Bayesian Network Structures. AISTATS 2018: 948-957 - [c31]Elias Jääsaari, Janne Leppä-aho, Tomi Silander, Teemu Roos:
Minimax Optimal Bayes Mixtures for Memoryless Sources over Large Alphabets. ALT 2018: 470-488 - [c30]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: 1113-1120 - [c29]Janne Leppä-aho, Santeri Räisänen, Xiao Yang, Teemu Roos:
Learning Non-parametric Markov Networks with Mutual Information. PGM 2018: 213-224 - [i9]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 abs/1811.11811 (2018) - [i8]Elias Jääsaari, Ville Hyvönen, Teemu Roos:
Efficient Autotuning of Hyperparameters in Approximate Nearest Neighbor Search. CoRR abs/1812.07484 (2018) - 2017
- [j18]Janne Leppä-aho, Johan Pensar, Teemu Roos, Jukka Corander:
Learning Gaussian graphical models with fractional marginal pseudo-likelihood. Int. J. Approx. Reason. 83: 21-42 (2017) - [j17]Yuan Zou, Teemu Roos:
On Model Selection, Bayesian Networks, and the Fisher Information Integral. New Gener. Comput. 35(1): 5-27 (2017) - [j16]Yuan Zou, Johan Pensar, Teemu Roos:
Representing local structure in Bayesian networks by Boolean functions. Pattern Recognit. Lett. 95: 73-77 (2017) - [r1]Teemu Roos:
Minimum Description Length Principle. Encyclopedia of Machine Learning and Data Mining 2017: 823-827 - [i7]Janne Leppä-aho, Santeri Räisänen, Xiao Yang, Teemu Roos:
Learning non-parametric Markov networks with mutual information. CoRR abs/1708.02497 (2017) - 2016
- [j15]Tuomas Heikkilä, Teemu Roos:
Thematic Section on Studia Stemmatologica. Digit. Scholarsh. Humanit. 31(3): 520-522 (2016) - [j14]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): 611-636 (2016) - [j13]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): 219-233 (2016) - [c28]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: 881-888 - [c27]Jussi Määttä, Teemu Roos:
Robust Sequential Prediction in Linear Regression with Student's t-distribution. ISAIM 2016 - [c26]Yuan Zou, Teemu Roos:
Sparse Logistic Regression with Logical Features. PAKDD (1) 2016: 316-327 - [c25]Yang Zhao, Sotiris K. Tasoulis, Teemu Roos:
Manifold Visualization via Short Walks. EuroVis (Short Papers) 2016: 85-89 - [i6]Janne Leppä-aho, Johan Pensar, Teemu Roos, Jukka Corander:
Learning Gaussian Graphical Models With Fractional Marginal Pseudo-likelihood. CoRR abs/1602.07863 (2016) - 2015
- [j12]Ralf Eggeling, Teemu Roos, Petri Myllymäki, Ivo Grosse:
Inferring intra-motif dependencies of DNA binding sites from ChIP-seq data. BMC Bioinform. 16: 375:1-375:15 (2015) - [j11]Kazuho Watanabe, Teemu Roos:
Achievability of asymptotic minimax regret by horizon-dependent and horizon-independent strategies. J. Mach. Learn. Res. 16: 2357-2375 (2015) - [c24]Quan Nguyen, Teemu Roos:
Likelihood-Based Inference of Phylogenetic Networks from Sequence Data by PhyloDAG. AlCoB 2015: 126-140 - [c23]Yuan Zou, Teemu Roos:
On Model Selection, Bayesian Networks, and the Fisher Information Integral. AMBN@JSAI-isAI 2015: 122-135 - [c22]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: 251-254 - [i5]Ville Hyvönen, Teemu Pitkänen, Sotiris K. Tasoulis, Liang Wang, Teemu Roos, Jukka Corander:
Fast k-NN search. CoRR abs/1509.06957 (2015) - 2014
- [c21]Ralf Eggeling, Teemu Roos, Petri Myllymäki, Ivo Grosse:
Robust learning of inhomogeneous PMMs. AISTATS 2014: 229-237 - [c20]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: 675-682 - [c19]Jussi Määttä, Samuli Siltanen, Teemu Roos:
A fixed-point image denoising algorithm with automatic window selection. EUVIP 2014: 1-6 - [c18]Andrew R. Barron, Teemu Roos, Kazuho Watanabe:
Bayesian properties of normalized maximum likelihood and its fast computation. ISIT 2014: 1667-1671 - [c17]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: 176-189 - [c16]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: 391 - [i4]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 abs/1401.0561 (2014) - [i3]Andrew R. Barron, Teemu Roos, Kazuho Watanabe:
Bayesian Properties of Normalized Maximum Likelihood and its Fast Computation. CoRR abs/1401.7116 (2014) - 2013
- [c15]Kazuho Watanabe, Teemu Roos, Petri Myllymäki:
Achievability of Asymptotic Minimax Regret in Online and Batch Prediction. ACML 2013: 181-196 - [c14]Antti Oulasvirta, Teemu Roos, Arttu Modig, Laura Leppänen:
Information capacity of full-body movements. CHI 2013: 1289-1298 - [c13]Teemu Roos, Yuan Zou:
Keep it simple stupid - On the effect of lower-order terms in BIC-like criteria. ITA 2013: 1-7 - 2012
- [j10]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): 1303-1304 (2012) - 2011
- [j9]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: 2181-2210 (2011) - [c12]Teemu Pulkkinen, Teemu Roos, Petri Myllymäki:
Semi-supervised Learning for WLAN Positioning. ICANN (1) 2011: 355-362 - [c11]Teemu Roos, Yuan Zou:
Analysis of Textual Variation by Latent Tree Structures. ICDM 2011: 567-576 - [i2]Teemu Roos, Antti Oulasvirta:
An Extended Framework for Measuring the Information Capacity of the Human Motor System. CoRR abs/1102.5225 (2011) - 2010
- [j8]Tomi Silander, Teemu Roos, Petri Myllymäki:
Learning locally minimax optimal Bayesian networks. Int. J. Approx. Reason. 51(5): 544-557 (2010) - [j7]Jorma Rissanen, Teemu Roos, Petri Myllymäki:
Model selection by sequentially normalized least squares. J. Multivar. Anal. 101(4): 839-849 (2010) - [c10]Po-Hsiang Lai, Teemu Roos, Joseph A. O'Sullivan:
MDL hierarchical clustering for stemmatology. ISIT 2010: 1403-1407
2000 – 2009
- 2009
- [j6]Teemu Roos, Tuomas Heikkilä:
Evaluating methods for computer-assisted stemmatology using artificial benchmark data sets. Lit. Linguistic Comput. 24(4): 417-433 (2009) - [j5]Teemu Roos, Petri Myllymäki, Jorma Rissanen:
MDL denoising revisited. IEEE Trans. Signal Process. 57(9): 3347-3360 (2009) - [c9]Teemu Roos, Bin Yu:
Sparse Markov source estimation via transformed Lasso. ITW 2009: 241-245 - [c8]Tomi Silander, Teemu Roos, Petri Myllymäki:
Locally Minimax Optimal Predictive Modeling with Bayesian Networks. AISTATS 2009: 504-511 - 2008
- [c7]Teemu Roos:
Monte Carlo estimation of minimax regret with an application to MDL model selection. ITW 2008: 284-288 - 2007
- [j4]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) - 2006
- [c6]Teemu Roos, Tuomas Heikkilä, Petri Myllymäki:
A Compression-Based Method for Stemmatic Analysis. ECAI 2006: 805-806 - [i1]Teemu Roos, Petri Myllymäki, Jorma Rissanen:
MDL Denoising Revisited. CoRR abs/cs/0609138 (2006) - 2005
- [j3]Teemu Roos, Hannes Wettig, Peter Grünwald, Petri Myllymäki, Henry Tirri:
On Discriminative Bayesian Network Classifiers and Logistic Regression. Mach. Learn. 59(3): 267-296 (2005) - [c5]Teemu Roos, Petri Myllymäki, Henry Tirri:
On the Behavior of MDL Denoising. AISTATS 2005: 309-316 - [c4]Teemu Roos, Peter Grünwald, Petri Myllymäki, Henry Tirri:
Generalization to Unseen Cases. BNAIC 2005: 194-201 - [c3]Teemu Roos, Peter Grünwald, Petri Myllymäki, Henry Tirri:
Generalization to Unseen Cases. NIPS 2005: 1129-1136 - 2004
- [c2]Petri Kontkanen, Petri Myllymäki, Teemu Roos, Henry Tirri, Kimmo Valtonen, Hannes Wettig:
Topics in probabilistic location estimation in wireless networks. PIMRC 2004: 1052-1056 - 2003
- [c1]Hannes Wettig, Peter Grünwald, Teemu Roos, Petri Myllymäki, Henry Tirri:
When Discriminative Learning of Bayesian Network Parameters Is Easy. IJCAI 2003: 491-498 - 2002
- [j2]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): 155-164 (2002) - [j1]Teemu Roos, Petri Myllymäki, Henry Tirri:
A Statistical Modeling Approach to Location Estimation. IEEE Trans. Mob. Comput. 1(1): 59-69 (2002)
Coauthor Index
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last updated on 2024-12-01 00:09 CET by the dblp team
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