An ICTP Hybrid meeting
“Youth in high-dimensions” gives to young researchers from academia and industry the opportunity to gather and present recent results on high-dimensional statistical problems, in areas ranging from machine learning and inference to neuroscience or statistical physics.
Typical problems in high-dimensions include estimating noisy signals (compressed sensing, PCA and tensor decomposition), analysing (deep) neural-networks, detecting communities in large networks, or modelling disordered spin systems. These seemingly unrelated problems share many similarities in their phenomenology and in the tools used to analyse them. The core of the field is made of a very active, diverse and quickly expanding community of physicists, computer scientists, mathematicians, information theorists and engineers, with the common desire to tackle increasingly challenging problems at the forefront of data science.
This conference aims at reinforcing the links among this interdisciplinary community, and in particular of its youngest theory-oriented members, and to bring forward the latest development happening in the high-dimensional world.
M. ALBERGO, New York University
E. BOIX-ADSERA, MIT
M. BUKOV, MPIKS Dresden
F. CAGNETTA, EPFL
F. CAMILLI, ICTP
K. CHANDRASEKHER, Stanford University
R. DUDEJA, Harvard University
S. FREI, UC Berkeley
F. GERACE, SISSA
R. GHEISSARI, Northwestern
S. GOEL, University of Pennsylvania
L. HRUZA, ENS Paris
A. JALAL, UC Berkeley
E. MATHIEU, University of Cambridge
S. PAPPALARDI, University of Köln
P. ROTONDO, University of Parma
B. SIMSEK, EPFL
J. TRINQUIER, ENS
Y. ZHANG, ISTA
Applicants are encouraged to submit an abstract for a poster presentation. During the application, please make sure to use our templates to format your abstract. Templates are available below for download.
Grants: A limited number of grants are available to support the attendance of selected participants, with priority given to participants from developing countries. There is no registration fee.