An information geometry perspective on estimation of distribution algorithms: boundary analysis. - Luigi Malagò; Matteo Matteucci; Bernardo Dal Seno (GECCO (Companion), 2008)

Evoptool: An extensible toolkit for evolutionary optimization algorithms comparison. - Gabriele Valentini; Luigi Malagò; Matteo Matteucci (IEEE Congress on Evolutionary Computation, 2010)

Stochastic Natural Gradient Descent by estimation of empirical covariances. - Luigi Malagò; Matteo Matteucci; Giovanni Pistone (IEEE Congress on Evolutionary Computation, 2011)

Introducing ℓ1-regularized logistic regression in Markov Networks based EDAs. - Luigi Malagò; Matteo Matteucci; Gabriele Valentini (IEEE Congress on Evolutionary Computation, 2011)

Towards the geometry of estimation of distribution algorithms based on the exponential family. - Luigi Malagò; Matteo Matteucci; Giovanni Pistone (FOGA, 2011)

Implicit Model Selection Based on Variable Transformations in Estimation of Distribution. - Emanuele Corsano; Davide A. Cucci; Luigi Malagò; Matteo Matteucci (LION, 2012)

Optimization by ℓ1-Constrained Markov Fitness Modelling. - Gabriele Valentini; Luigi Malagò; Matteo Matteucci (LION, 2012)

Variable Transformations in Estimation of Distribution Algorithms. - Davide A. Cucci; Luigi Malagò; Matteo Matteucci (PPSN (1), 2012)

On the geometry of optimization based on the exponential family relaxation. - Luigi Malagò (2012)

Natural gradient, fitness modelling and model selection: A unifying perspective. - Luigi Malagò; Matteo Matteucci; Giovanni Pistone (IEEE Congress on Evolutionary Computation, 2013)

Robust Estimation of Natural Gradient in Optimization by Regularized Linear Regression. - Luigi Malagò; Matteo Matteucci (GSI, 2013)

Information geometry in evolutionary computation. - Luigi Malagò; Tobias Glasmachers (GECCO (Companion), 2014)

Combinatorial Optimization with Information Geometry: The Newton Method. - Luigi Malagò; Giovanni Pistone (Entropy, 2014)

Information Geometry of the Gaussian Distribution in View of Stochastic Optimization. - Luigi Malagò; Giovanni Pistone (FOGA, 2015)

Second-Order Optimization over the Multivariate Gaussian Distribution. - Luigi Malagò; Giovanni Pistone (GSI, 2015)

Natural Gradient Flow in the Mixture Geometry of a Discrete Exponential Family. - Luigi Malagò; Giovanni Pistone (Entropy, 2015)

Tutorials at PPSN 2016. - Carola Doerr; Nicolas Bredèche; Enrique Alba 001; Thomas Bartz-Beielstein; Dimo Brockhoff; Benjamin Doerr; Gusz Eiben; Michael G. Epitropakis; Carlos M. Fonseca; Andreia P. Guerreiro; Evert Haasdijk; Jacqueline Heinerman; et al. (PPSN, 2016)

Learning in Variational Autoencoders with Kullback-Leibler and Renyi Integral Bounds. - Septimia Sârbu; Riccardo Volpi; Alexandra Peste; Luigi Malagò (CoRR, 2018)

Variational autoencoders trained with q-deformed lower bounds. - Septimia Sârbu; Luigi Malagò (DGS@ICLR, 2019)

Parameters Estimation for the Cosmic Microwave Background with Bayesian Neural Networks. - Héctor J. Hortúa; Riccardo Volpi; Dimitri Marinelli; Luigi Malagò (CoRR, 2019)

Natural Alpha Embeddings. - Riccardo Volpi; Luigi Malagò (CoRR, 2019)

Tumor Detection in Brain MRIs by Computing Dissimilarities in the Latent Space of a Variational AutoEncoder. - Alexandra-Ioana Albu; Alina Enescu; Luigi Malagò (NLDL, 2020)

Evaluating the Robustness of Defense Mechanisms based on AutoEncoder Reconstructions against Carlini-Wagner Adversarial Attacks. - Petru Hlihor; Riccardo Volpi; Luigi Malagò (NLDL, 2020)

Evaluating Natural Alpha Embeddings on Intrinsic and Extrinsic Tasks. - Riccardo Volpi; Luigi Malagò (RepL4NLP@ACL, 2020)

Parameters Estimation from the 21 cm signal using Variational Inference. - Héctor J. Hortúa; Riccardo Volpi; Luigi Malagò (CoRR, 2020)

Improved Slice-wise Tumour Detection in Brain MRIs by Computing Dissimilarities between Latent Representations. - Alexandra-Ioana Albu; Alina Enescu; Luigi Malagò (CoRR, 2020)

Natural Wake-Sleep Algorithm. - Csongor Várady; Riccardo Volpi; Luigi Malagò; Nihat Ay (CoRR, 2020)

Reliable Uncertainties for Bayesian Neural Networks using Alpha-divergences. - Héctor J. Hortúa; Luigi Malagò; Riccardo Volpi (CoRR, 2020)

Lagrangian and Hamiltonian Mechanics for Probabilities on the Statistical Manifold. - Goffredo Chirco; Luigi Malagò; Giovanni Pistone (CoRR, 2020)

Accelerating MCMC algorithms through Bayesian Deep Networks. - Héctor J. Hortúa; Riccardo Volpi; Dimitri Marinelli; Luigi Malagò (CoRR, 2020)

Constraining the Reionization History using Bayesian Normalizing Flows. - Héctor J. Hortúa; Luigi Malagò; Riccardo Volpi (Mach. Learn. Sci. Technol., 2020)

Automatic Feature Extraction for Heartbeat Anomaly Detection. - Robert-George Colt; Csongor-Huba Várady; Riccardo Volpi; Luigi Malagò (CoRR, 2021)

Changing the Geometry of Representations: α-Embeddings for NLP Tasks. - Riccardo Volpi; Uddhipan Thakur; Luigi Malagò (Entropy, 2021)

Natural Reweighted Wake-Sleep. - Csongor Várady; Riccardo Volpi; Luigi Malagò; Nihat Ay (Neural Networks, 2022)