Teemu Roos - RankMe

88 papers A* 7A 7B 7C 1Misc 2Journal 48Unranked 15

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	Breakable Machine: A K-12 Classroom Game for Transformative AI Literacy Through Spoofing and eXplainable AI (XAI). AAAI Olli Hilke, Nicolas Pope, Juho Kahila, Henriikka Vartiainen, Teemu Roos, Tuomo Parkki, Matti Tedre
2026	J	`jnl`	Deterministic and probabilistic neural surrogates of global hybrid-Vlasov simulations. CoRR Daniel Holmberg, Ivan Zaitsev, Markku Alho, Ioanna Bouri, Fanni Franssila, Haewon Jeong, Minna Palmroth, Teemu Roos
2026	J	`jnl`	LEMUR: Learned Multi-Vector Retrieval. CoRR Elias Jääsaari, Ville Hyvönen, Teemu Roos
2025	A*	`conf`	An XAI Social Media Platform for Teaching K-12 Students AI-Driven Profiling, Clustering, and Engagement-Based Recommending. AAAI Nicolas Pope, Juho Kahila, Henriikka Vartiainen, Mohammed Saqr, Sonsoles López-Pernas, Teemu Roos, Jari Laru, Matti Tedre
2025	J	`jnl`	Breakable Machine: A K-12 Classroom Game for Transformative AI Literacy Through Spoofing and eXplainable AI (XAI). CoRR Olli Hilke, Nicolas Pope, Juho Kahila, Henriikka Vartiainen, Teemu Roos, Tuomo Parkki, Matti Tedre
2025	—	`conf`	Failure as a Learning Opportunity in AI Literacy. Koli Calling Olli Hilke, Nicolas Pope, Juho Kahila, Henriikka Vartiainen, Teemu Roos, Tuomo Parkki, Matti Tedre
2025	J	`jnl`	Graph-based Neural Space Weather Forecasting. CoRR Daniel Holmberg, Ivan Zaitsev, Markku Alho, Ioanna Bouri, Fanni Franssila, Haewon Jeong, Minna Palmroth, Teemu Roos
2025	J	`jnl`	VIBE: Vector Index Benchmark for Embeddings. CoRR Elias Jääsaari, Ville Hyvönen, Matteo Ceccarello, Teemu Roos, Martin Aumüller
2024	J	`jnl`	A Multilabel Classification Framework for Approximate Nearest Neighbor Search. J. Mach. Learn. Res. Ville Hyvönen, Elias Jääsaari, Teemu Roos
2024	B	`conf`	An Educational Tool for Learning about Social Media Tracking, Profiling, and Recommendation. ICALT Nicolas Pope, Juho Kahila, Jari Laru, Henriikka Vartiainen, Teemu Roos, Matti Tedre
2024	J	`jnl`	An Educational Tool for Learning about Social Media Tracking, Profiling, and Recommendation. CoRR Nicolas Pope, Juho Kahila, Jari Laru, Henriikka Vartiainen, Teemu Roos, Matti Tedre
2024	J	`jnl`	An XAI Social Media Platform for Teaching K-12 Students AI-Driven Profiling, Clustering, and Engagement-Based Recommending. CoRR Nicolas Pope, Juho Kahila, Henriikka Vartiainen, Mohammed Saqr, Sonsoles López-Pernas, Teemu Roos, Jari Laru, Matti Tedre
2024	A*	`conf`	LoRANN: Low-Rank Matrix Factorization for Approximate Nearest Neighbor Search. NeurIPS Elias Jääsaari, Ville Hyvönen, Teemu Roos
2024	J	`jnl`	LoRANN: Low-Rank Matrix Factorization for Approximate Nearest Neighbor Search. CoRR Elias Jääsaari, Ville Hyvönen, Teemu Roos
2024	J	`jnl`	Modeling 3D Infant Kinetics Using Adaptive Graph Convolutional Networks. CoRR Daniel Holmberg, Manu Airaksinen, Viviana Marchi, Andrea Guzzetta, Anna Kivi, Leena M. Haataja, Sampsa Vanhatalo, Teemu Roos
2024	J	`jnl`	Quotient Normalized Maximum Likelihood Criterion for Learning Bayesian Network Structures. CoRR Tomi Silander, Janne Leppä-aho, Elias Jääsaari, Teemu Roos
2024	J	`jnl`	Regional Ocean Forecasting with Hierarchical Graph Neural Networks. CoRR Daniel Holmberg, Emanuela Clementi, Teemu Roos
2023	J	`jnl`	Graph Representation of the Magnetic Field Topology in High-Fidelity Plasma Simulations for Machine Learning Applications. CoRR Ioanna Bouri, Fanni Franssila, Markku Alho, Giulia Cozzani, Ivan Zaitsev, Minna Palmroth, Teemu Roos
2023	J	`jnl`	Transfer Learning with Ensembles of Deep Neural Networks for Skin Cancer Detection in Imbalanced Data Sets. Neural Process. Lett. Aqsa Saeed Qureshi, Teemu Roos
2022	A*	`conf`	A Multilabel Classification Framework for Approximate Nearest Neighbor Search. NeurIPS Ville Hyvönen, Elias Jääsaari, Teemu Roos
2021	J	`jnl`	Gradient-based training and pruning of radial basis function networks with an application in materials physics. Neural Networks Jussi Määttä, Viacheslav Bazaliy, Jyri Kimari, Flyura Djurabekova, Kai Nordlund, Teemu Roos
2021	J	`jnl`	Transfer Learning with Ensembles of Deep Neural Networks for Skin Cancer Classification in Imbalanced Data Sets. CoRR Aqsa Saeed Qureshi, Teemu Roos
2020	J	`jnl`	Gradient-Based Training and Pruning of Radial Basis Function Networks with an Application in Materials Physics. CoRR Jussi Määttä, Viacheslav Bazaliy, Jyri Kimari, Flyura Djurabekova, Kai Nordlund, Teemu Roos
2020	J	`jnl`	Nonlinear dimensionality reduction for clustering. Pattern Recognit. Sotiris K. Tasoulis, Nicos G. Pavlidis, Teemu Roos
2019	—	`conf`	Efficient Autotuning of Hyperparameters in Approximate Nearest Neighbor Search. PAKDD (2) Elias Jääsaari, Ville Hyvönen, Teemu Roos
2019	J	`jnl`	Minimum Description Length Revisited. CoRR Peter Grünwald, Teemu Roos
2019	J	`jnl`	Supervised Learning Approach to Approximate Nearest Neighbor Search. CoRR Ville Hyvönen, Elias Jääsaari, Teemu Roos
2018	—	`conf`	An Application of Storage-Optimal MatDot Codes for Coded Matrix Multiplication: Fast k-Nearest Neighbors Estimation. IEEE BigData Utsav Sheth, Sanghamitra Dutta, Malhar Chaudhari, Haewon Jeong, Yaoqing Yang, Jukka Kohonen, Teemu Roos, Pulkit Grover
2018	J	`jnl`	An Application of Storage-Optimal MatDot Codes for Coded Matrix Multiplication: Fast k-Nearest Neighbors Estimation. CoRR Utsav Sheth, Sanghamitra Dutta, Malhar Chaudhari, Haewon Jeong, Yaoqing Yang, Jukka Kohonen, Teemu Roos, Pulkit Grover
2018	J	`jnl`	Efficient Autotuning of Hyperparameters in Approximate Nearest Neighbor Search. CoRR Elias Jääsaari, Ville Hyvönen, Teemu Roos
2018	—	`conf`	Learning Non-parametric Markov Networks with Mutual Information. PGM Janne Leppä-aho, Santeri Räisänen, Xiao Yang, Teemu Roos
2018	B	`conf`	Minimax Optimal Bayes Mixtures for Memoryless Sources over Large Alphabets. ALT Elias Jääsaari, Janne Leppä-aho, Tomi Silander, Teemu Roos
2018	J	`jnl`	Quantitative methods for the analysis of medieval calendars. Digit. Scholarsh. Humanit. Tuomas Heikkilä, Teemu Roos
2018	A	`conf`	Quotient Normalized Maximum Likelihood Criterion for Learning Bayesian Network Structures. AISTATS Tomi Silander, Janne Leppä-aho, Elias Jääsaari, Teemu Roos
2017	J	`jnl`	Learning Gaussian graphical models with fractional marginal pseudo-likelihood. Int. J. Approx. Reason. Janne Leppä-aho, Johan Pensar, Teemu Roos, Jukka Corander
2017	J	`jnl`	Learning non-parametric Markov networks with mutual information. CoRR Janne Leppä-aho, Santeri Räisänen, Xiao Yang, Teemu Roos
2017	—	`ch.`	Minimum Description Length Principle. Encyclopedia of Machine Learning and Data Mining Teemu Roos
2017	J	`jnl`	On Model Selection, Bayesian Networks, and the Fisher Information Integral. New Gener. Comput. Yuan Zou, Teemu Roos
2017	J	`jnl`	Representing local structure in Bayesian networks by Boolean functions. Pattern Recognit. Lett. Yuan Zou, Johan Pensar, Teemu Roos
2016	—	`conf`	Fast nearest neighbor search through sparse random projections and voting. IEEE BigData Ville Hyvönen, Teemu Pitkänen, Sotiris K. Tasoulis, Elias Jaasaari, Risto Tuomainen, Liang Wang, Jukka Corander, Teemu Roos
2016	J	`jnl`	Kvasir: Scalable Provision of Semantically Relevant Web Content on Big Data Framework. IEEE Trans. Big Data Liang Wang, Sotiris K. Tasoulis, Teemu Roos, Jussi Kangasharju
2016	J	`jnl`	Learning Gaussian Graphical Models With Fractional Marginal Pseudo-likelihood. CoRR Janne Leppä-aho, Johan Pensar, Teemu Roos, Jukka Corander
2016	—	`conf`	Manifold Visualization via Short Walks. EuroVis (Short Papers) Yang Zhao, Sotiris K. Tasoulis, Teemu Roos
2016	J	`jnl`	Oral fairy tale or literary fake? Investigating the origins of Little Red Riding Hood using phylogenetic network analysis. Digit. Scholarsh. Humanit. Jamshid Tehrani, Quan Nguyen, Teemu Roos
2016	Misc	`conf`	Robust Sequential Prediction in Linear Regression with Student's t-distribution. ISAIM Jussi Määttä, Teemu Roos
2016	—	`conf`	Sparse Logistic Regression with Logical Features. PAKDD (1) Yuan Zou, Teemu Roos
2016	J	`jnl`	Thematic Section on Studia Stemmatologica. Digit. Scholarsh. Humanit. Tuomas Heikkilä, Teemu Roos
2015	J	`jnl`	Achievability of asymptotic minimax regret by horizon-dependent and horizon-independent strategies. J. Mach. Learn. Res. Kazuho Watanabe, Teemu Roos
2015	J	`jnl`	Fast k-NN search. CoRR Ville Hyvönen, Teemu Pitkänen, Sotiris K. Tasoulis, Liang Wang, Teemu Roos, Jukka Corander
2015	J	`jnl`	Inferring intra-motif dependencies of DNA binding sites from ChIP-seq data. BMC Bioinform. Ralf Eggeling, Teemu Roos, Petri Myllymäki, Ivo Grosse
2015	—	`conf`	Kvasir: Seamless Integration of Latent Semantic Analysis-Based Content Provision into Web Browsing. WWW (Companion Volume) Liang Wang, Sotiris K. Tasoulis, Teemu Roos, Jussi Kangasharju
2015	—	`conf`	Likelihood-Based Inference of Phylogenetic Networks from Sequence Data by PhyloDAG. AlCoB Quan Nguyen, Teemu Roos
2015	—	`conf`	On Model Selection, Bayesian Networks, and the Fisher Information Integral. AMBN@JSAI-isAI Yuan Zou, Teemu Roos
2014	—	`conf`	A fixed-point image denoising algorithm with automatic window selection. EUVIP Jussi Määttä, Samuli Siltanen, Teemu Roos
2014	J	`jnl`	Bayesian Properties of Normalized Maximum Likelihood and its Fast Computation. CoRR Andrew R. Barron, Teemu Roos, Kazuho Watanabe
2014	B	`conf`	Bayesian properties of normalized maximum likelihood and its fast computation. ISIT Andrew R. Barron, Teemu Roos, Kazuho Watanabe
2014	—	`conf`	Random projection based clustering for population genomics. IEEE BigData Sotiris K. Tasoulis, Lu Cheng, Niko Välimäki, Nicholas J. Croucher, Simon R. Harris, William P. Hanage, Teemu Roos, Jukka Corander
2014	A	`conf`	Robust learning of inhomogeneous PMMs. AISTATS Ralf Eggeling, Teemu Roos, Petri Myllymäki, Ivo Grosse
2014	J	`jnl`	User-Generated Free-Form Gestures for Authentication: Security and Memorability. CoRR Michael Sherman, Gradeigh Clark, Yulong Yang, Shridatt Sugrim, Arttu Modig, Janne Lindqvist, Antti Oulasvirta, Teemu Roos
2014	A	`conf`	User-generated free-form gestures for authentication: security and memorability. MobiSys Michael Sherman, Gradeigh Clark, Yulong Yang, Shridatt Sugrim, Arttu Modig, Janne Lindqvist, Antti Oulasvirta, Teemu Roos
2014	A	`conf`	Video: User-generated free-form gestures for authentication: security and memorability. MobiSys Michael Sherman, Gradeigh Clark, Yulong Yang, Shridatt Sugrim, Arttu Modig, Janne Lindqvist, Antti Oulasvirta, Teemu Roos
2013	C	`conf`	Achievability of Asymptotic Minimax Regret in Online and Batch Prediction. ACML Kazuho Watanabe, Teemu Roos, Petri Myllymäki
2013	A*	`conf`	Information capacity of full-body movements. CHI Antti Oulasvirta, Teemu Roos, Arttu Modig, Laura Leppänen
2013	Misc	`conf`	Keep it simple stupid - On the effect of lower-order terms in BIC-like criteria. ITA Teemu Roos, Yuan Zou
2012	J	`jnl`	Special Issue on the Fifth European Workshop on Probabilistic Graphical Models (PGM-2010). Int. J. Approx. Reason. Teemu Roos, Petri Myllymäki, Tommi S. Jaakkola
2011	J	`jnl`	An Extended Framework for Measuring the Information Capacity of the Human Motor System CoRR Teemu Roos, Antti Oulasvirta
2011	A*	`conf`	Analysis of Textual Variation by Latent Tree Structures. ICDM Teemu Roos, Yuan Zou
2011	J	`jnl`	Discriminative Learning of Bayesian Networks via Factorized Conditional Log-Likelihood. J. Mach. Learn. Res. Alexandra M. Carvalho, Teemu Roos, Arlindo L. Oliveira, Petri Myllymäki
2011	—	`conf`	Semi-supervised Learning for WLAN Positioning. ICANN (1) Teemu Pulkkinen, Teemu Roos, Petri Myllymäki
2010	J	`jnl`	Learning locally minimax optimal Bayesian networks. Int. J. Approx. Reason. Tomi Silander, Teemu Roos, Petri Myllymäki
2010	B	`conf`	MDL hierarchical clustering for stemmatology. ISIT Po-Hsiang Lai, Teemu Roos, Joseph A. O'Sullivan
2010	J	`jnl`	Model selection by sequentially normalized least squares. J. Multivar. Anal. Jorma Rissanen, Teemu Roos, Petri Myllymäki
2009	J	`jnl`	Evaluating methods for computer-assisted stemmatology using artificial benchmark data sets. Lit. Linguistic Comput. Teemu Roos, Tuomas Heikkilä
2009	A	`conf`	Locally Minimax Optimal Predictive Modeling with Bayesian Networks. AISTATS Tomi Silander, Teemu Roos, Petri Myllymäki
2009	J	`jnl`	MDL denoising revisited. IEEE Trans. Signal Process. Teemu Roos, Petri Myllymäki, Jorma Rissanen
2009	B	`conf`	Sparse Markov source estimation via transformed Lasso. ITW Teemu Roos, Bin Yu
2008	B	`conf`	Monte Carlo estimation of minimax regret with an application to MDL model selection. ITW Teemu Roos
2007	J	`jnl`	Information Theoretic Methods for Bioinformatics. EURASIP J. Bioinform. Syst. Biol. Jorma Rissanen, Peter D. Grünwald, Jukka Heikkonen, Petri Myllymäki, Teemu Roos, Juho Rousu
2006	A	`conf`	A Compression-Based Method for Stemmatic Analysis. ECAI Teemu Roos, Tuomas Heikkilä, Petri Myllymäki
2006	J	`jnl`	MDL Denoising Revisited CoRR Teemu Roos, Petri Myllymäki, Jorma Rissanen
2005	—	`conf`	Generalization to Unseen Cases. BNAIC Teemu Roos, Peter Grünwald, Petri Myllymäki, Henry Tirri
2005	—	`conf`	Generalization to Unseen Cases. NIPS Teemu Roos, Peter Grünwald, Petri Myllymäki, Henry Tirri
2005	J	`jnl`	On Discriminative Bayesian Network Classifiers and Logistic Regression. Mach. Learn. Teemu Roos, Hannes Wettig, Peter Grünwald, Petri Myllymäki, Henry Tirri
2005	A	`conf`	On the Behavior of MDL Denoising. AISTATS Teemu Roos, Petri Myllymäki, Henry Tirri
2004	B	`conf`	Topics in probabilistic location estimation in wireless networks. PIMRC Petri Kontkanen, Petri Myllymäki, Teemu Roos, Henry Tirri, Kimmo Valtonen, Hannes Wettig
2003	A*	`conf`	When Discriminative Learning of Bayesian Network Parameters Is Easy. IJCAI Hannes Wettig, Peter Grünwald, Teemu Roos, Petri Myllymäki, Henry Tirri
2002	J	`jnl`	A Probabilistic Approach to WLAN User Location Estimation. Int. J. Wirel. Inf. Networks Teemu Roos, Petri Myllymäki, Henry Tirri, Pauli Misikangas, Juha Sievänen
2002	J	`jnl`	A Statistical Modeling Approach to Location Estimation. IEEE Trans. Mob. Comput. Teemu Roos, Petri Myllymäki, Henry Tirri