Sustainability and Machine Learning Group
Sustainability and Machine Learning Group
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Towards self-certified learning: Probabilistic neural networks trained by PAC-Bayes with Backprop
Marı́a 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
,
Marı́a Pérez-Ortiz
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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 P. Deisenroth
,
K. S. Sesh Kumar
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On the Gromov-Wasserstein distance and Coupled Deep Generative Models
Samuel Cohen
,
Dino Sejdinovic
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Variational Integrator Networks
Steindór Sæmundsson
,
Katja Hofmann
,
Marc Deisenroth
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Fast Decomposable Submodular Function Minimization using Constrained Total Variation
We consider the problem of minimizing the sum of submodular set functions assuming minimization oracles of each summand function. Most …
K. S. Sesh Kumar
,
F. Bach
,
T. Pock
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Deep Gaussian Processes with Importance-Weighted Variational Inference
Hugh Salimbeni
,
Vincent Dutordoir
,
James Hensman
,
Marc P. Deisenroth
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Code
Exploiting Synthetically Generated Data with Semi-Supervised Learning for Small and Imbalanced Datasets
Maria Perez-Ortiz
,
Peter Tino
,
Rafal Mantiuk
,
Cesar Hervas-Martinez
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