Luigi Malag˛
Luigi Malag˛
Transylvanian Institute of Neuroscience (TINS), Cluj-Napoca, Romania
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Cited by
Cited by
Wasserstein Riemannian geometry of Gaussian densities
L Malag˛, L Montrucchio, G Pistone
Information Geometry 1, 137-179, 2018
Information geometry of the Gaussian distribution in view of stochastic optimization
L Malag˛, G Pistone
Proceedings of the 2015 ACM Conference on Foundations of Genetic Algorithmsá…, 2015
Towards the geometry of estimation of distribution algorithms based on the exponential family
L Malag˛, M Matteucci, G Pistone
Proceedings of the 11th workshop proceedings on Foundations of geneticá…, 2011
Parameter estimation for the cosmic microwave background with Bayesian neural networks
HJ Hort˙a, R Volpi, D Marinelli, L Malag˛
Physical Review D 102 (10), 103509, 2020
Constraining the reionization history using Bayesian normalizing flows
HJ Hort˙a, L Malag˛, R Volpi
Machine Learning: Science and Technology 1 (3), 035014, 2020
Natural gradient, fitness modelling and model selection: A unifying perspective
L Malago, M Matteucci, G Pistone
2013 IEEE Congress on Evolutionary Computation, 486-493, 2013
Combinatorial optimization with information geometry: The Newton method
L Malag˛, G Pistone
Entropy 16 (8), 4260-4289, 2014
Online active learning with strong and weak annotators
L Malago, N Cesa-Bianchi, J Renders
NIPS Workshop on Learning from the Wisdom of Crowds, 2014
Stochastic relaxation as a unifying approach in 0/1 programming
L Malago, M Matteucci, G Pistone
NIPS 2009 workshop on discrete optimization in machine learningá…, 2009
Natural gradient flow in the mixture geometry of a discrete exponential family
L Malag˛, G Pistone
Entropy 17 (6), 4215-4254, 2015
Stochastic natural gradient descent by estimation of empirical covariances
M Luigi, M Matteo, G Pistone
2011 IEEE Congress of Evolutionary Computation (CEC), 949-956, 2011
Lagrangian and Hamiltonian dynamics for probabilities on the statistical bundle
G Chirco, L Malag˛, G Pistone
International Journal of Geometric Methods in Modern Physics 19 (13), 2250214, 2022
Introducing ℓ1-regularized logistic regression in Markov Networks based EDAs
M Luigi, M Matteucci, G Valentini
2011 IEEE Congress of Evolutionary Computation (CEC), 1581-1588, 2011
A note on the border of an exponential family
L Malago, G Pistone
arXiv preprint arXiv:1012.0637 1, 2010
An information geometry perspective on estimation of distribution algorithms: boundary analysis
L Malag˛, M Matteucci, B Dal Seno
Proceedings of the 10th annual conference companion on Genetic andá…, 2008
Evoptool: an extensible toolkit for evolutionary optimization algorithms comparison
G Valentini, L Malago, M Matteucci
IEEE Congress on Evolutionary Computation, 1-8, 2010
Natural wake-sleep algorithm
C Vßrady, N Ay, R Volpi, L Malag˛
Evaluating the robustness of defense mechanisms based on autoencoder reconstructions against carlini-wagner adversarial attacks
P Hlihor, R Volpi, L Malag˛
Proceedings of the Northern Lights Deep Learning Workshop 1, 6-6, 2020
On the geometry of optimization based on the exponential family relaxation
L Malago
Politecnico di Milano, 2012
Optimization by ℓ1-Constrained Markov Fitness Modelling
G Valentini, L Malag˛, M Matteucci
Learning and Intelligent Optimization: 6th International Conference, LION 6á…, 2012
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