4 citations · 9 across the 8 of their papers we have counts for
9 papers
Robust dimension-free estimation of simple random tensors: optimal guarantees under heavy tails and adversarial contamination
Roberto I. Oliveira, Zoraida F. Rico, Philip Thompson
We study robust estimation of simple random tensors of arbitrary order under finite-moment assumptions and adversarial contamination. We propose the first robust e…
Debiasing the Lasso under Weaker Tail Assumptions
Leonardo Voltarelli, Roberto Imbuzeiro Oliveira
We consider the problem of high-dimensional inference with the lasso estimator. Different methods including 'double selection' techniques and multiple versions of the 'debiased las…
Nonparametric inference on Fokker-Plank and McKean-Vlasov models
Adriana Laurindo Monteiro, Roberto Imbuzeiro Oliveira
We propose a kernel-based estimator of the velocity field governing the transport and diffusion of -dimensional interacting particles. Assuming the initial positions are i.i.d.…
Trimmed sample means for robust uniform mean estimation and regression
Roberto I. Oliveira, Lucas Resende
It is well-known that trimmed sample means are robust against heavy tails and data contamination. This paper analyzes the performance of trimmed means and related methods in two no…
A spectral least-squares-type method for heavy-tailed corrupted regression with unknown covariance \& heterogeneous noise
Roberto I. Oliveira, Zoraida F. Rico, Philip Thompson
We revisit heavy-tailed corrupted least-squares linear regression assuming to have a corrupted -sized label-feature sample of at most arbitrary outliers. We wish to estimat…
Improved covariance estimation: optimal robustness and sub-Gaussian guarantees under heavy tails
Roberto I. Oliveira, Zoraida F. Rico
We present an estimator of the covariance matrix of random -dimensional vector from an i.i.d. sample of size . Our sole assumption is that this vector satisfies a bounded…
Large deviations for marked sparse random graphs with applications to interacting diffusions
Rangel Baldasso, Roberto I Oliveira, Alan Pereira +1
We consider the empirical neighborhood distribution of marked sparse Erdős-Rényi random graphs, obtained by decorating edges and vertices of a sparse Erdős-Rényi random graph with…
Split Conformal Prediction and Non-Exchangeable Data
Roberto I. Oliveira, Paulo Orenstein, Thiago Ramos +1
Split conformal prediction (CP) is arguably the most popular CP method for uncertainty quantification, enjoying both academic interest and widespread deployment. However, the origi…
Disparity of clustering coefficients in the Holme-Kim network model
Roberto I. Oliveira, Rodrigo B. Ribeiro, Remy Sanchis
The Holme-Kim random graph processes is a variant of the Barabasi-Albert scale-free graph that was designed to exhibit clustering. In this paper we show that whether the model does…