*Speaker: Maksym Byshkin *Title: Fast Maximum Likelihood estimation via Equilibrium Expectation for Large Network Data *Abstract: Network data may be analyzed by constructing statistical models that accurately reproduce the data features that may be of theoretical relevance or empirical interest. Examples of such models are Exponential Random Graph Models for social networks and Markov Random Field for image processing. Typically, Markov chain Monte Carlo (MCMC) methods are used when normalizing constants of statistical models cannot be computed. We propose a new approach for the Maximum Likelihood Estimation (MLE) of parameters of statistical models with intractable normalizing constants. The approach we propose relies on properties of Markov chains at equilibrium and, for this reason, we call it Equilibrium Expectation (EE). Using this approach we design a simple and fast algorithm to find MLE when it exists and is unique. Good scaling properties of the algorithm allow dramatic increase of the size of dependent/network data for which MLE may be computed. Application of the algorithm to large size images, biological and social networks is presented. Application to Restricted Boltzmann machines and similar data-generating models is discussed. *Bio: Maksym Byshkin is a postdoctoral researcher at Università della Svizzera italiana (USI), where he serves also as a lectures and teaches Data Science. His research fields are statistical physics, statistical network analysis, Monte Carlo methods, computational chemistry and interdisciplinary collaborations. The research activity and research interests are focused on developments of empirical models and computational methods for high performance computing. Maksym holds a Master degree in applied mathematics and a Doctoral degree in theoretical physics from the Kharkov Institute of Physics and Technology (Landau school). Before joining USI he spent several years as a postdoctoral research fellow at the Free University of Brussels and the University of Salerno. *When: Wednesday 25th of July 2018, 12:00-13:00 *Location: Manno, Galleria 1, 2nd floor, room G1-204 *Registration: Pizza (or alternative food) and drinks will be offered at the end of the talk. If you plan to attend, please register in a timely fashion at the following link so that we will have no shortage of food: https://doodle.com/poll/vy5cxiibugeznwuw