MATHEMATICAL ASPECTS OF LEARNING THEORY: Poster session

MATHEMATICAL ASPECTS OF LEARNING THEORY: Posters

Not provided	Antonio Álvarez (Universidad Autónoma de Madrid)
Computational lower bounds for multi-frequency group synchronization	Anastasia Kireeva (ETH Zurich)
Semiparametric Generative Invariance	Carlos García Meixide (Instituto de Ciencias Matemáticas)
Empirical Approximation of the Gaussian Distribution in Rd	Daniel Bartl (University of Viena)
Generalized Resubstitution for Error Estimation in Regression	Diego Marcondes (University of Sao Paulo)
Near-Optimal Learning and Planning in Separated Latent MDPs	Fan Chen (MIT)
Minimum Norm Interpolation Meets The Local Theory of Banach Spaces	Gil Kur (ETH Zürich)
Benign Overfitting of Interpolating Linear Classifiers on non-Subgaussian Mixtures	Ichiro Hashimoto (University of Toronto)
Emergence of collective learning in coupled deep neural nets	Lluís Arola-Fernández (IFISC, CSIC-UIB)
Projected-L0 Decoder for Variable Selection in Linear Regression	Maxim Fedotov (Universitat Pompeu Fabra)
A framework for robustifying linear regression models against adversarial manipulations	Pablo García Arce (ICMAT)
Online Model Selection	Parnian Kassraie ( Swiss Federal Institute of Technology in Zurich)
Higher-order matrix concentration inequalities	Petar Nizic-Nikolac (ETH Zurich)
Path weights in concentration graphs	Robert Castelo (Universitat Pompeu Fabra)
Is complexity an invariant of the representation base?	V. Abadie (ETH Zurich)
On a general theory for bootstrap-based hypothesis testing	Wieger Schipper (Delft University of Technology)
Deep neural networks learn cellular automaton rules in many-valued logic	Yani Zhang (ETH Zurich)

MATHEMATICAL ASPECTS OF LEARNING THEORY