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Unsupervised Learning
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Unsupervised Learning
Group Robust Classification Without Any Group Information
Empirical risk minimization (ERM) is sensitive to spurious correlations present in training data, which poses a significant risk when …
Christos Tsirigotis
,
João Monteiro
,
Pau Rodriguez
,
Aaron Courville
Conference on Neural Information Processing Systems (NeurIPS), 2023.
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Choreographer: Learning and Adapting Skills in Imagination
Unsupervised skill learning aims to learn a rich repertoire of behaviors without external supervision, providing artificial agents with …
Pietro Mazzaglia
,
Tim Verbelen
,
Bart Dhoedt
,
Alexandre Lacoste
,
Sai Rajeswar Mudumba
International Conference of Learning Representations (ICLR), 2023.
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Choreographer: Learning and Adapting Skills in Imagination
Unsupervised skill learning aims to learn a rich repertoire of behaviors without external supervision, providing artificial agents with …
Pietro Mazzaglia
,
Tim Verbelen
,
Bart Dhoedt
,
Alexandre Lacoste
,
Sai Rajeswar Mudumba
Workshop at the Neural Information Processing Systems (NeurIPS), 2022.
PDF
Citation
Code
Overcoming challenges in leveraging GANs for few-shot data augmentation
In this paper, we explore the use of GAN-based few-shot data augmentation as a method to improve few-shot classification performance. …
Christopher Beckham
,
Issam H. Laradji
,
Pau Rodriguez
,
David Vazquez
,
Derek Nowrouzezahrai
,
Christopher Pal
Workshop at the Conference on Lifelong Learning Agents (CoLLAs), 2022.
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Citation
Unsupervised Model-based Pre-training for Data-efficient Reinforcement Learning from Pixels
Reinforcement learning (RL) aims at autonomously performing complex tasks. To this end, a reward signal is used to steer the learning …
Sai Rajeswar Mudumba
,
Pietro Mazzaglia
,
Tim Verbelen
,
Alexandre Piche
,
Aaron Courville
,
Alexandre Lacoste
Workshop at the International Conference on Machine Learning (ICML), 2022.
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Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data
Remote sensing and automatic earth monitoring are key to solve global-scale challenges such as disaster prevention, land use …
Oscar Manas
,
Alexandre Lacoste
,
Xavier Giro-i-Nieto
,
David Vazquez
,
Pau Rodriguez
International Conference on Computer Vision (ICCV), 2021.
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Unsupervised Learning of Dense Visual Representations
Contrastive self-supervised learning has emerged as a promising approach to unsupervised visual representation learning. In general, …
Pedro O. Pinheiro
,
Amjad Almahairi
,
Ryan Benmalek
,
Florian Golemo
,
Aaron Courville
Conference on Neural Information Processing Systems (NeurIPS), 2020.
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A Closer Look at the Optimization Landscapes of Generative Adversarial Networks
Generative adversarial networks have been very successful in generative modeling, however they remain relatively challenging to train …
Hugo Berard
,
Gauthier Gidel
,
Amjad Almahairi
,
Pascal Vincent
,
Simon Lacoste-Julien
International Conference on Learning Representations (ICLR), 2020.
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Neocortical plasticity: an unsupervised cake but no free lunch
The fields of artificial intelligence and neuroscience have a long history of fertile bi-directional interactions. On the one hand, …
Eilif Muller
,
Philippe Beaudoin
Workshop at the Neural Information Processing Systems (NeurIPS), 2019.
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On Adversarial Mixup Resynthesis
In this paper, we explore new approaches to combining information encoded within the learned representations of auto-encoders. We …
Christopher Beckham
,
Sina Honari
,
Vikas Verma
,
Alex Lamb
,
Farnoosh Ghadiri
,
R Devon Hjelm
,
Yoshua Bengio
,
Christopher Pal
Conference on Neural Information Processing Systems (NeurIPS), 2019.
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