1 citations · 1 across the 4 of their papers we have counts for
4 papers
Improved Concentration for Mean Estimators via Shrinkage
Antônio Catão, Lucas Resende, Paulo Orenstein
We study a class of robust mean estimators obtained by adaptively shrinking the weights of sample points far from a base estimator . Given a data-dependent s…
Statistical Inference in Large Multi-way Networks
Lucas Resende, Guillaume Lecué, Lionel Wilner +1
We propose the Polyads estimator, a new method to estimate structural parameters in weighted multi-way networks while controlling for rich, arbitrary structures of fixed effects. T…
Robust high-dimensional Gaussian and bootstrap approximations for trimmed sample means
Lucas Resende
Robust mean estimation has largely focused on concentration guarantees under heavy tails and contamination. We study robustness from a different perspective: high-dimensional Gauss…
Deep Hashing via Householder Quantization
Lucas R. Schwengber, Lucas Resende, Paulo Orenstein +1
Hashing is at the heart of large-scale image similarity search, and recent methods have been substantially improved through deep learning techniques. Such algorithms typically lear…