2 citations · 3 across the 4 of their papers we have counts for
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Safe Screening Rules for -Regression
Alper Atamtürk, Andrés Gómez
We give safe screening rules to eliminate variables from regression with regularization or cardinality constraint. These rules are based on guarantees that a feature may o…
Learning Optimal Classification Trees: Strong Max-Flow Formulations
Sina Aghaei, Andres Gomez, Phebe Vayanos
We consider the problem of learning optimal binary classification trees. Literature on the topic has burgeoned in recent years, motivated both by the empirical suboptimality of heu…
Rank-one Convexification for Sparse Regression
Alper Atamturk, Andres Gomez
Sparse regression models are increasingly prevalent due to their ease of interpretability and superior out-of-sample performance. However, the exact model of sparse regression with…
Sparse and Smooth Signal Estimation: Convexification of L0 Formulations
Alper Atamturk, Andres Gomez, Shaoning Han
Signal estimation problems with smoothness and sparsity priors can be naturally modeled as quadratic optimization with -"norm" constraints. Since such problems are non-conv…