Pierre-antoine Manzagol
8 papers · 2005–2021 · 4 venues · across top CS/AI venues
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Achievements
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π£ Hot Topic Early Bird π Academic Marathon Β· Full π Interdisciplinary Bridge Β· Bronze πΊοΈ Taxonomy Completionist (22) π Conference Polyglot Β· Bronze
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Topic Pioneer
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Keyword Pioneer
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Trend Setter
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The Questioner
Venues
Top co-authors
Research topics
Machine Learning
(7)
Deep Learning
(5)
Learning Types Β· Machine Learning
(5)
Optimization & Theory Β· Machine Learning
(4)
Artificial Intelligence
(2)
Mathematics & Optimization
(2)
Architectures
(2)
Optimization
(2)
Optimization & Theory Β· Deep Learning
(2)
Core AI
(1)
Core Methods
(1)
Learning Paradigms
(1)
Learning Types Β· Deep Learning
(1)
Techniques
(1)
Keywords
stochastic gradient descent
(2)
stochastic optimization
(1)
representation learning
(1)
multi-task learning
(1)
feature learning
(1)
few-shot learning
(1)
online learning
(1)
large-scale optimization
(1)
transfer learning
(1)
unsupervised pretraining
(1)
code generation
(1)
natural gradient
(1)
fisher information
(1)
graph-based learning
(1)
generalization error
(1)
source code
(1)
online optimization
(1)
variance reduction
(1)
natural gradient descent
(1)
online approximation
(1)
Papers
PLUR: A Unifying, Graph-Based View of Program Learning, Understanding, and Repair
NeurIPS 2021
Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples
ICLR 2020
On the interplay between noise and curvature and its effect on optimization and generalization
AISTATS 2020
Reducing the variance in online optimization by transporting past gradients
NeurIPS 2019
Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion
JMLR 2010
Why Does Unsupervised Pre-training Help Deep Learning?
JMLR 2010
Topmoumoute Online Natural Gradient Algorithm
NeurIPS 2007
The Difficulty of Training Deep Architectures and the Effect of Unsupervised Pre-Training
AISTATS 2005