Luigi Malagò

According to our database1, Luigi Malagò authored at least 30 papers between 2008 and 2021.

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Bibliography

2021
Changing the Geometry of Representations: α-Embeddings for NLP Tasks.
Entropy, 2021

Automatic Feature Extraction for Heartbeat Anomaly Detection.
CoRR, 2021

2020
Constraining the Reionization History using Bayesian Normalizing Flows.
Mach. Learn. Sci. Technol., 2020

Accelerating MCMC algorithms through Bayesian Deep Networks.
CoRR, 2020

Lagrangian and Hamiltonian Mechanics for Probabilities on the Statistical Manifold.
CoRR, 2020

Reliable Uncertainties for Bayesian Neural Networks using Alpha-divergences.
CoRR, 2020

Natural Wake-Sleep Algorithm.
CoRR, 2020

Improved Slice-wise Tumour Detection in Brain MRIs by Computing Dissimilarities between Latent Representations.
CoRR, 2020

Parameters Estimation from the 21 cm signal using Variational Inference.
CoRR, 2020

Evaluating Natural Alpha Embeddings on Intrinsic and Extrinsic Tasks.
Proceedings of the 5th Workshop on Representation Learning for NLP, 2020

2019
Natural Alpha Embeddings.
CoRR, 2019

Parameters Estimation for the Cosmic Microwave Background with Bayesian Neural Networks.
CoRR, 2019

Variational autoencoders trained with q-deformed lower bounds.
Proceedings of the Deep Generative Models for Highly Structured Data, 2019

2018
Learning in Variational Autoencoders with Kullback-Leibler and Renyi Integral Bounds.
CoRR, 2018

2016

2015
Natural Gradient Flow in the Mixture Geometry of a Discrete Exponential Family.
Entropy, 2015

Second-Order Optimization over the Multivariate Gaussian Distribution.
Proceedings of the Geometric Science of Information - Second International Conference, 2015

Information Geometry of the Gaussian Distribution in View of Stochastic Optimization.
Proceedings of the 2015 ACM Conference on Foundations of Genetic Algorithms XIII, Aberystwyth, United Kingdom, January 17, 2015

2014
Combinatorial Optimization with Information Geometry: The Newton Method.
Entropy, 2014

Information geometry in evolutionary computation.
Proceedings of the Genetic and Evolutionary Computation Conference, 2014

2013
Robust Estimation of Natural Gradient in Optimization by Regularized Linear Regression.
Proceedings of the Geometric Science of Information - First International Conference, 2013

Natural gradient, fitness modelling and model selection: A unifying perspective.
Proceedings of the IEEE Congress on Evolutionary Computation, 2013

2012
Variable Transformations in Estimation of Distribution Algorithms.
Proceedings of the Parallel Problem Solving from Nature - PPSN XII, 2012

Optimization by ℓ1-Constrained Markov Fitness Modelling.
Proceedings of the Learning and Intelligent Optimization - 6th International Conference, 2012

Implicit Model Selection Based on Variable Transformations in Estimation of Distribution.
Proceedings of the Learning and Intelligent Optimization - 6th International Conference, 2012

2011
Towards the geometry of estimation of distribution algorithms based on the exponential family.
Proceedings of the Foundations of Genetic Algorithms, 11th International Workshop, 2011

Introducing ℓ1-regularized logistic regression in Markov Networks based EDAs.
Proceedings of the IEEE Congress on Evolutionary Computation, 2011

Stochastic Natural Gradient Descent by estimation of empirical covariances.
Proceedings of the IEEE Congress on Evolutionary Computation, 2011

2010
Evoptool: An extensible toolkit for evolutionary optimization algorithms comparison.
Proceedings of the IEEE Congress on Evolutionary Computation, 2010

2008
An information geometry perspective on estimation of distribution algorithms: boundary analysis.
Proceedings of the Genetic and Evolutionary Computation Conference, 2008


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