ACM.Īntti Kangasrääsiö, Yi Chen, Dorota Glowacka, and Samuel Kaski (2016). 732-740.Īntti Kangasrääsiö, Yi Chen, Dorota Glowacka, Samuel Kaski (2016).ĭealing with Concept Drift in Exploratory Search: An Interactive Bayesian Approach.
The 19th International Conference on Artificial Intelligence and Statistics, JMLR W&CP, pp. Non-Stationary Gaussian Process Regression with Hamiltonian Monte Carlo. Markus Heinonen, Henrik Mannerström, Juho Rousu, Samuel Kaski, Harri Lähdesmäki (2016). Journal of Machine Learning Research, 17:1-35. Multiple Output Regression with Latent Noise. Havulinna, Marjo-Riitta Järvelin, Mika Ala-Korpela, Samuel Kaski (2016). Kangas, Pasi Soininen, Mehreen Ali, Aki S.
Jussi Gillberg, Pekka Marttinen, Matti Pirinen, Antti J. In Proceedings of IJCAI-16, the Twenty-Fifth International Joint Conference on Artificial Intelligence Junning Gao, Makoto Yamada, Samuel Kaski, Hiroshi Mamitsuka, Shanfeng Zhu (2016).Ī robust convex formulation for ensemble clustering. Natural brain-information interfaces: Recommending information by relevance inferred from human brain signals. Spapé, Oswald Barral, Niklas Ravaja, Giulio Jacucci, Samuel Kaski (2016). In Proceedings of the 21st International Conference on Intelligent User Interfaces (IUI '16). Interactive intent modeling from multiple feedback domains. Pedram Daee, Joel Pyykkö, Dorota Glowacka, and Samuel Kaski (2016). Probabilistic Expert Knowledge Elicitation of Feature Relevances in Sparse Linear Regression. Pedram Daee, Tomi Peltola, Marta Soare and Samuel Kaski (2016). MetaCCA: Summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis. Raitakari, Marjo-Riitta Järvelin, Veikko Salomaa, Mika Ala-Korpela, Samuli Ripatti, Matti Pirinen (2016). Kangas, Pasi Soininen, Terho Lehtimäki, Olli T. 2457-2463.Īnna Cichonska, Juho Rousu, Pekka Marttinen, Antti J. Sparse group factor analysis for biclustering of multiple data sources. Kerstin Bunte, Eemeli Leppäaho, Inka Saarinen, Samuel Kaski (2016). Modelling-based experiment retrieval: A case study with gene expression clustering. Paul Blomstedt, Ritabrata Dutta, Sohan Seth, Alvis Brazma and Samuel Kaski (2016). User Modeling and User-Adapted Interaction, 26:493-520, 2016. Eugster, Niklas Ravaja, Samuel Kaski, and Giulio Jacucci (2016).Įxtracting relevance and affect information from physiological text annotation. Oswald Barral, Ilkka Kosunen, Tuukka Ruotsalo, Michiel M. In FILM 2016, NIPS Workshop on Future of Interactive Learning Machines.
Regression Analysis in Small-n-Large-p Using Interactive Prior Elicitation of Pairwise Similarities. Homayun Afrabandpey, Tomi Peltola, Samuel Kaski. Kernelized Bayesian Matrix Factorization. Murumägi, Olli Kallioniemi, Tero Aittokallio and Samuel Kaski (2016).ĭrug response prediction by inferring pathway-response associations with Muhammad Ammad-ud-din, Suleiman A.Khan, Disha Malani, Astrid Order publications (2017-) by: Publication year Title First author For the earlier publications of these groups, please see below. The group is a fusion of two former research groups from Aalto University, the Statistical Machine Learning and Bioinformatics group and the Bayesian Methodology group. This page lists the publications of the Probabilistic Machine Learning group formed in 2015.