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Sample-efficient reinforcement learning using deep Gaussian processes


Nov 02, 2020
Charles Gadd, Markus Heinonen, Harri Lähdesmäki, Samuel Kaski


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Differentially Private Bayesian Inference for Generalized Linear Models


Nov 01, 2020
Tejas Kulkarni, Joonas Jälkö, Antti Koskela, Samuel Kaski, Antti Honkela


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Scalable Bayesian neural networks by layer-wise input augmentation


Oct 26, 2020
Trung Trinh, Samuel Kaski, Markus Heinonen

* 8 pages 

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Rethinking pooling in graph neural networks


Oct 22, 2020
Diego Mesquita, Amauri H. Souza, Samuel Kaski

* Accepted to NeurIPS 2020 

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Bayesian Inference for Optimal Transport with Stochastic Cost


Oct 19, 2020
Anton Mallasto, Markus Heinonen, Samuel Kaski


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Privacy-preserving Data Sharing on Vertically Partitioned Data


Oct 19, 2020
Razane Tajeddine, Joonas Jälkö, Samuel Kaski, Antti Honkela


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Teaching to Learn: Sequential Teaching of Agents with Inner States


Sep 14, 2020
Mustafa Mert Celikok, Pierre-Alexandre Murena, Samuel Kaski


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Differentially private cross-silo federated learning


Jul 10, 2020
Mikko A. Heikkilä, Antti Koskela, Kana Shimizu, Samuel Kaski, Antti Honkela

* 14 pages, 5 figures 

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Likelihood-Free Inference with Deep Gaussian Processes


Jun 18, 2020
Alexander Aushev, Henri Pesonen, Markus Heinonen, Jukka Corander, Samuel Kaski


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Human Strategic Steering Improves Performance of Interactive Optimization


May 04, 2020
Fabio Colella, Pedram Daee, Jussi Jokinen, Antti Oulasvirta, Samuel Kaski

* 10 pages, 5 figures, The paper is published in the proceedings of UMAP 2020. Codes available at https://github.com/fcole90/interactive_bayesian_optimisation 

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