Publications


Selected papers appear in bold

Papers in International Journals


  • L. Malagò, L. Montrucchio, and G. Pistone.
    Wasserstein Riemannian Geometry of Positive Definite Matrices.
    In Information Geometry, Volume 1, Issue 2, pp 137-179, 2018

  • L. Malagò and G. Pistone.
    Natural Gradient Flow in the Mixture Geometry of a Discrete Exponential Family.
    In Entropy 17(6), special issue on Information, Entropy and their Geometric Structures, 4215-4254, 2015

  • L. Malagò and G. Pistone.
    Combinatorial Optimization with Information Geometry: Newton Method.
    In Entropy 16(8), special issue on Information Geometry, pages 4260-4289, 2014.

  • Papers in Proceedings of International Conferences


  • L. Malagò and G. Pistone.
    Second-Order Optimization over the Multivariate Gaussian Distribution.
    In Geometric Science of Information GSI, 2015.

  • L. Malagò and G. Pistone.
    Information Geometry of Gaussian Distributions in View of Stochastic Optimization.
    Proceedings of FOGA '15, held on January 17-20, 2015, Aberystwyth, Wales, 2015.

  • L. Malagò and G. Pistone.
    Gradient Flow of the Stochastic Relaxation on a Generic Exponential Family.
    Proceedings of MaxEnt 2014, held on September 21-26, 2014, Château Clos Lucé, Amboise, France, 2014.
    Extra material: [animation]

  • L. Malagò and G. Pistone.
    Optimization via Information Geometry.
    In Book of Proceedings of the Seventh International Workshop on Simulation (IWS) held on May 21-25, 2013, in Rimini, Italy, 2014.

  • L. Malagò and M. Matteucci.
    Robust Estimation of Natural Gradient in Optimization by Regularized Linear Regression.
    In Geometric Science of Information GSI2013, 2013.

  • L. Malagò, M. Matteucci, and G. Pistone.
    Natural Gradient, Fitness Modelling and Model Selection: A Unifying Perspective.
    In IEEE Congress on Evolutionary Computation (CEC), 2013.

  • D. Cucci, L. Malagò and M. Matteucci.
    Variable Transformations in Estimation of Distribution Algorithms.
    In Parallel Problem Solving from Nature - PPSN XII, Lecture Notes in Computer Science Volume 7491, pages 428--437, 2012.

  • E. Corsano, D. Cucci, L. Malagò, and M. Matteucci.
    Implicit Model Selection based on Variable Transformations in Estimation of Distribution.
    In Learning and Intelligent OptimizatioN Conference LION 6, Lecture Notes in Computer Science, pages 360--365, 2012.

  • G. Valentini, L. Malagò, and M. Matteucci.
    Optimization by l1-constrained Markov fitness modelling.
    In Learning and Intelligent OptimizatioN Conference LION 6, Lecture Notes in Computer Science, pages 250--264, 2012.

  • L. Malagò, M. Matteucci, and G. Pistone.
    Optimization of pseudo-boolean functions by stochastic natural gradient descent.
    In MIC 2011, 9th Metaheuristics International Conference, 2011.

  • L. Malagò, M. Matteucci, and G. Valentini.
    Introducing l1-regularized logistic regression in Markov networks based EDAs.
    In Evolutionary Computation (CEC), 2011 IEEE Congress on, pages 1581--1588, 2011.

  • L. Malagò, M. Matteucci, and G. Pistone.
    Stochastic natural gradient descent by estimation of empirical covariances.
    In Evolutionary Computation (CEC), 2011 IEEE Congress on, pages 949--956, 2011.

  • L. Malagò, M. Matteucci, and G. Pistone.
    Towards the geometry of estimation of distribution algorithms based on the exponential family.
    In Proceedings of FOGA '11, pages 230--242, New York, NY, USA, 2011. ACM.

  • G. Valentini, L. Malagò, and M. Matteucci.
    Evoptool: An extensible toolkit for evolutionary optimization algorithms comparison.
    In Evolutionary Computation (CEC), 2010 IEEE Congress on, pages 1--8, 2010.

  • A. Bonarini, A. Furlan, L. Malagò, D. Marzorati, M. Matteucci, D. Migliore, M. Restelli, and D. G. Sorrenti.
    Milan Robocup Team 2009.
    Robocup International Symposium 2009, Robocup 2009, Graz, Austria, pages 1--8, 2009.

  • Papers in Workshops


  • L. Malagò, Nicolò Cesa-Bianchi, and Jean-Michel Renders.
    Online Active Learning with Strong and Weak Annotators
    .
    NIPS 2014 Workshop on Crowdsourcing and Machine Learning, Montreal, Canada, 13 December 2014.

  • L. Malagò, and G. Pistone.
    Stochastic Relaxation over the Exponential Family: Second-Order Geometry.
    NIPS 2014 Workshop on Optimization for Machine Learning (OPT2014), Montreal, Canada, 12 December 2014.

  • L. Malagò and G. Pistone.
    A note on the border of an exponential family.
    Working paper, Carlo Alberto Notebooks, No. 168. A shorter version of the paper was presented at the SIS 2010 conference in Padova, Italy. [arXiv:1012.0637]

  • L. Malagò, M. Matteucci and G. Pistone.
    Stochastic relaxation as a unifying approach in 0/1 programming.
    NIPS 2009 Workshop on Discrete Optimization in Machine Learning: Submodularity, Sparsity & Polyhedra (DISCML), Whistler, Canada, 2009.

  • L. Malagò, M. Matteucci, and B. Dal Seno.
    An information geometry perspective on estimation of distribution algorithms: boundary analysis.
    In Proceedings of the 2008 GECCO conference companion on Genetic and evolutionary computation, GECCO '08, pages 2081--2088, New York, NY, USA, 2008. ACM.

  • Other contributions


  • R. Barboza, L. Borra, M. B. Criniti, L. Malagò, and M. Rossi.
    IERoKi, Innovative Entertainment Robot for Kids.
    In Multidisciplinarity and Innovation, ASP projects 1, Alta Scuola Politecnica, pages 56--59. Telesma Edizioni, 2007.
    Extra material: [video]


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