
Events
If you want to receive updates on RoMaDS activities, write an email to salvi(at)mat.uniroma2.it to be added to our mailing list.
Upcoming events
05.02.2025 - Seminar: Stefano Favaro (Università di Torino), A smoothed-Bayesian approach to frequency recovery from sketched data14h00-15h00, Department of Mathematics, Aula Dal Passo.
Abstract
We introduce a novel statistical perspective on a classical problem at the intersection of computer science and information theory: recovering the empirical frequency of a symbol in a large discrete dataset using only a compressed representation, or sketch, obtained via random hashing. Departing from traditional algorithmic approaches, recent works have proposed Bayesian nonparametric (BNP) methods that can provide more informative frequency estimates by leveraging modeling assumptions on the distribution of the sketched data. In this paper, we propose a smoothed-Bayesian method, inspired by existing BNP approaches but designed in a frequentist framework to overcome the computational limitations of the BNP approaches when dealing with large-scale data from realistic distributions, including those with power-law tail behaviors. For sketches obtained with a single hash function, our approach is supported by frequentist guarantees, including unbiasedness and optimality under a squared error loss function within a class of linear estimators. For sketches with multiple hash functions, we introduce an approach based on multi-view learning to construct computationally efficient frequency estimators. We validate our method on synthetic and real data, comparing its performance to that of existing alternatives.
Joint work with Mario Beraha (Politecnico di Milano) and Matteo Sesia (University of Southern California)
10.02.2025 - Double Seminar: Alexandre Stauffer (King's College London), Non-monotone phase transition in interacting particle systems
+ Jacopo Borga (MIT), Lattice Yang-Mills theory in the large N limit via sums over surfaces
14h00-16h00, Department of Mathematics, Aula Dal Passo.
Abstract Stauffer
In this talk we will discuss a reaction-diffusion particle system which has a non-monotone phase transition.
I will explain the techniques used to analyze monotone models and how they can be refined to
analyze non-monotone particle systems.
Based on upcoming works with Leandro Chiarini and Tom Finn.
Abstract Borga
Lattice Yang-Mills theories are important models in particle physics. They are defined on the d-dimensional lattice Z^d using a group of matrices of dimension N, and Wilson loop expectations are the fundamental observables of these theories. Recently, Cao, Park, and Sheffield showed that Wilson loop expectations can be expressed as sums over certain embedded bipartite maps of any genus. Building on this novel approach, we prove in the so-called strongly coupled regime:
- A rigorous formula in terms of embedded bipartite planar maps of Wilson loop expectations in the large N limit, in any dimension d.
- An exact computation of Wilson loop expectations in the large N limit, in dimension d=2, for a large family of (simple and non-simple) loops.
Previous results to the two aforementioned points were previously established by Chatterjee (2019) and Basu & Ganguly (2016), respectively. Our results extend these previous results, offer simpler proofs and provide a new perspective on these significant quantities.
This work is a collaboration with Sky Cao and Jasper Shogren-Knaak.
07-11.04.2025 - Mini-course: Johannes Schmidt-Hieber (University of Twente), Title TBA
Department of Mathematics, Aula Dal Passo.
Schedule: Mon 14:00-16:30 Wed 14:00-16:30 Fri 14:00-16:30.
Abstract
TBA
May-June 2025 - PhD course: Quentin Berger (Université Sorbonne Paris Nord), Statistical mechanics and disordered systems
Schedule TBA, Department of Mathematics, Aula Dal Passo.
Abstract
In the first part of the course course, I will review some models of
statistical mechanics and discuss a central question in the study of
disordered systems, the so-called disorder relevance. This question is
quite broad and mainly consists in determining whether the properties of a
system are stable under small (random) perturbations or whether they are
affected by the presence of a small noise.
For the rest of the course I will develop at length an example: the Directed
Polymer Model.
The Directed Polymer Model is based on a Simple Random Walk
interacting with a random environment, and it has seen an incredible
activity (and important progress) over the past decade. In fact, even though
the model is very simply defined (it is a disordered version of the simple
random walk), it exhibits a wide range of behaviours and in particular it
undergoes a phase transition as the intensity of disorder varies.
I will first describe important features of this model, for instance showing
the presence of a phase transition and discussing the role of the dimension
in the question of disorder relevance. I will then present very recent result
on several fronts:
• the recent characterization of the phase transition in dimension d≥3,
• the construction of a disordered scaling limit and its relation to the
Stochastic Heat Equation,
• the case of the critical dimension d=2.
