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Gabriel Arpino

3 accepted papers

2024

Inferring Change Points in High-Dimensional Linear Regression via Approximate Message Passing

ICML 2024poster

We consider the problem of localizing change points in high-dimensional linear regression. We propose an Approximate Message Passing (AMP) algorithm for estimating both the signals and the change point locations. Assuming Gaussian covariates, we give an exact asymptotic characterization of its estim…

Cited by 4SourcePDFScholar
2021

On the Role of Data in PAC-Bayes Bounds

AISTATS 2021poster

The dominant term in PAC-Bayes bounds is often the Kullback-Leibler divergence between the posterior and prior. For so-called linear PAC-Bayes risk bounds based on the empirical risk of a fixed posterior kernel, it is possible to minimize the expected value of the bound by choosing the prior to be t…

2018

Using Information Invariants to Compare Swarm Algorithms and General Multi-Robot Algorithms

ICRA 2018poster

Robotic swarms are decentralized multi-robot systems whose members use local information from proximal neighbors to execute simple reactive control laws that result in emergent collective behaviors. In contrast, members of a general multi-robot system may have access to global information, all-to-al…

Cited by 3SourceScholar