3 papers
cs.LG2026
Representation Gap: Explaining the Unreasonable Effectiveness of Neural Networks from a Geometric Perspective
David Perera, Victor Moura, Lais Isabelle Alves dos Santos +2
Characterizing precisely the asymptotic generalization error of neural networks using parameters that can be estimated efficiently is a crucial problem in machine learning, which r…
stat.ME2026
Density-valued VAR Models with Latent Factors
Yasumasa Matsuda, Michel F. C. Haddad
We propose a density-valued vector autoregressive model with latent factors for multivariate time series of density functions. Motivated by weekly regional distributions of SARS-Co…
cs.LG2024
Adaptive -nearest neighbor classifier based on the local estimation of the shape operator
Alexandre Luís Magalhães Levada, Frank Nielsen, Michel Ferreira Cardia Haddad
The -nearest neighbor (-NN) algorithm is one of the most popular methods for nonparametric classification. However, a relevant limitation concerns the definition of the numbe…