Sustainability and Machine Learning Group
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Sparse Parallel Training of Hierarchical Dirichlet Process Topic Models
Nonparametric extensions of topic models such as Latent Dirichlet Allocation, including Hierarchical Dirichlet Process (HDP), are often …
Alexander Terenin
,
Måns Magnusson
,
Leif Jonsson
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SUM'20: State-based User Modelling
Sahan Bulathwela
,
María Pérez-Ortiz
,
Rishabh Mehrotra
,
Davor Orlic
,
Colin De La Higuera
,
John Shawe-Taylor
,
Emine Yilmaz
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Towards self-certified learning: Probabilistic neural networks trained by PAC-Bayes with Backprop
María Pérez-Ortiz
,
Omar Rivasplata
,
John Shawe-Taylor
,
Csaba Szepesvári
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TrueLearn: A Family of Bayesian Algorithms to Match Lifelong Learners to Open Educational Resources
Sahan Bulathwela
,
Maria Perez-Ortiz
,
Emine Yilmaz
,
John Shawe-Taylor
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What's in it for me? Augmenting Recommended Learning Resources with Navigable Annotations
Sahan Bulathwela
,
Stefan Kreitmayer
,
María Pérez-Ortiz
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On the Gromov-Wasserstein distance and Coupled Deep Generative Models
Samuel Cohen
,
Dino Sejdinovic
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Disentangled Skill Embeddings for Reinforcement Learning
Janith C. Petangoda
,
Sergio Pascoal-Diaz
,
Vincent Adam
,
Peter Vrancx
,
Jordi Grau-Moya
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High-Dimensional Bayesian Optimization Using Low-Dimensional Feature Spaces
Riccardo Moriconi
,
Marc Deisenroth
,
K. S. Sesh Kumar
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Variational Integrator Networks
Steindór Sæmundsson
,
Katja Hofmann
,
Marc Deisenroth
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Variational Integrator Networks for Physically Meaningful Embeddings
Steindór Sæmundsson
,
Alexander Terenin
,
Katja Hofmann
,
Marc Deisenroth
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