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