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2020 – today
- 2022
[j5]Csongor Várady
, Riccardo Volpi, Luigi Malagò, Nihat Ay:
Natural Reweighted Wake-Sleep. Neural Networks 155: 574-591 (2022)- 2021
- [j4]Riccardo Volpi, Uddhipan Thakur, Luigi Malagò:
Changing the Geometry of Representations: α-Embeddings for NLP Tasks. Entropy 23(3): 287 (2021) - [i11]Robert-George Colt, Csongor-Huba Várady, Riccardo Volpi, Luigi Malagò:
Automatic Feature Extraction for Heartbeat Anomaly Detection. CoRR abs/2102.12289 (2021) - 2020
- [j3]Héctor J. Hortúa, Luigi Malagò, Riccardo Volpi:
Constraining the Reionization History using Bayesian Normalizing Flows. Mach. Learn. Sci. Technol. 1(3): 35014 (2020) - [c18]Alexandra-Ioana Albu, Alina Enescu, Luigi Malagò:
Tumor Detection in Brain MRIs by Computing Dissimilarities in the Latent Space of a Variational AutoEncoder. NLDL 2020: 1-6 - [c17]Petru Hlihor, Riccardo Volpi, Luigi Malagò:
Evaluating the Robustness of Defense Mechanisms based on AutoEncoder Reconstructions against Carlini-Wagner Adversarial Attacks. NLDL 2020: 1-6 - [c16]Riccardo Volpi, Luigi Malagò:
Evaluating Natural Alpha Embeddings on Intrinsic and Extrinsic Tasks. RepL4NLP@ACL 2020: 61-71 - [i10]Héctor J. Hortúa, Riccardo Volpi, Luigi Malagò:
Parameters Estimation from the 21 cm signal using Variational Inference. CoRR abs/2005.02299 (2020) - [i9]Héctor J. Hortúa, Luigi Malagò, Riccardo Volpi:
Constraining the Reionization History using Bayesian Normalizing Flows. CoRR abs/2005.07694 (2020) - [i8]Alexandra-Ioana Albu, Alina Enescu, Luigi Malagò:
Improved Slice-wise Tumour Detection in Brain MRIs by Computing Dissimilarities between Latent Representations. CoRR abs/2007.12528 (2020) - [i7]Csongor Várady, Riccardo Volpi, Luigi Malagò, Nihat Ay:
Natural Wake-Sleep Algorithm. CoRR abs/2008.06687 (2020) - [i6]Héctor J. Hortúa, Luigi Malagò, Riccardo Volpi:
Reliable Uncertainties for Bayesian Neural Networks using Alpha-divergences. CoRR abs/2008.06729 (2020) - [i5]Goffredo Chirco, Luigi Malagò, Giovanni Pistone:
Lagrangian and Hamiltonian Mechanics for Probabilities on the Statistical Manifold. CoRR abs/2009.09431 (2020) - [i4]Héctor J. Hortúa, Riccardo Volpi, Dimitri Marinelli, Luigi Malagò:
Accelerating MCMC algorithms through Bayesian Deep Networks. CoRR abs/2011.14276 (2020)
2010 – 2019
- 2019
- [c15]Septimia Sârbu, Luigi Malagò:
Variational autoencoders trained with q-deformed lower bounds. DGS@ICLR 2019 - [i3]Héctor J. Hortúa, Riccardo Volpi, Dimitri Marinelli, Luigi Malagò:
Parameters Estimation for the Cosmic Microwave Background with Bayesian Neural Networks. CoRR abs/1911.08508 (2019) - [i2]Riccardo Volpi, Luigi Malagò:
Natural Alpha Embeddings. CoRR abs/1912.02280 (2019) - 2018
- [i1]Septimia Sârbu, Riccardo Volpi, Alexandra Peste, Luigi Malagò:
Learning in Variational Autoencoders with Kullback-Leibler and Renyi Integral Bounds. CoRR abs/1807.01889 (2018) - 2016
- [c14]Carola Doerr, Nicolas Bredèche, Enrique Alba, Thomas Bartz-Beielstein, Dimo Brockhoff, Benjamin Doerr, Gusz Eiben, Michael G. Epitropakis, Carlos M. Fonseca, Andreia P. Guerreiro, Evert Haasdijk, Jacqueline Heinerman, Julien Hubert, Per Kristian Lehre, Luigi Malagò, Juan Julián Merelo Guervós, Julian Francis Miller, Boris Naujoks, Pietro S. Oliveto, Stjepan Picek, Nelishia Pillay, Mike Preuss, Patricia Ryser-Welch, Giovanni Squillero, Jörg Stork, Dirk Sudholt, Alberto Paolo Tonda, L. Darrell Whitley, Martin Zaefferer:
Tutorials at PPSN 2016. PPSN 2016: 1012-1022 - 2015
- [j2]Luigi Malagò, Giovanni Pistone:
Natural Gradient Flow in the Mixture Geometry of a Discrete Exponential Family. Entropy 17(6): 4215-4254 (2015) - [c13]Luigi Malagò, Giovanni Pistone:
Information Geometry of the Gaussian Distribution in View of Stochastic Optimization. FOGA 2015: 150-162 - [c12]Luigi Malagò, Giovanni Pistone:
Second-Order Optimization over the Multivariate Gaussian Distribution. GSI 2015: 349-358 - 2014
- [j1]Luigi Malagò, Giovanni Pistone:
Combinatorial Optimization with Information Geometry: The Newton Method. Entropy 16(8): 4260-4289 (2014) - [c11]Luigi Malagò, Tobias Glasmachers:
Information geometry in evolutionary computation. GECCO (Companion) 2014: 709-726 - 2013
- [c10]Luigi Malagò, Matteo Matteucci, Giovanni Pistone:
Natural gradient, fitness modelling and model selection: A unifying perspective. IEEE Congress on Evolutionary Computation 2013: 486-493 - [c9]Luigi Malagò, Matteo Matteucci:
Robust Estimation of Natural Gradient in Optimization by Regularized Linear Regression. GSI 2013: 861-867 - 2012
- [b1]Luigi Malagò:
On the geometry of optimization based on the exponential family relaxation. Polytechnic University of Milan, Italy, 2012 - [c8]Gabriele Valentini, Luigi Malagò, Matteo Matteucci:
Optimization by ℓ1-Constrained Markov Fitness Modelling. LION 2012: 250-264 - [c7]Emanuele Corsano, Davide A. Cucci, Luigi Malagò, Matteo Matteucci:
Implicit Model Selection Based on Variable Transformations in Estimation of Distribution. LION 2012: 360-365 - [c6]Davide A. Cucci, Luigi Malagò, Matteo Matteucci:
Variable Transformations in Estimation of Distribution Algorithms. PPSN (1) 2012: 428-437 - 2011
- [c5]Luigi Malagò, Matteo Matteucci, Giovanni Pistone:
Stochastic Natural Gradient Descent by estimation of empirical covariances. IEEE Congress on Evolutionary Computation 2011: 949-956 - [c4]Luigi Malagò, Matteo Matteucci, Gabriele Valentini:
Introducing ℓ1-regularized logistic regression in Markov Networks based EDAs. IEEE Congress on Evolutionary Computation 2011: 1581-1588 - [c3]Luigi Malagò, Matteo Matteucci, Giovanni Pistone:
Towards the geometry of estimation of distribution algorithms based on the exponential family. FOGA 2011: 230-242 - 2010
- [c2]Gabriele Valentini, Luigi Malagò, Matteo Matteucci:
Evoptool: An extensible toolkit for evolutionary optimization algorithms comparison. IEEE Congress on Evolutionary Computation 2010: 1-8
2000 – 2009
- 2008
- [c1]Luigi Malagò, Matteo Matteucci, Bernardo Dal Seno:
An information geometry perspective on estimation of distribution algorithms: boundary analysis. GECCO (Companion) 2008: 2081-2088
Coauthor Index
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