ODTLearn is an open-source Python package that provides methods for lear...
We study the problem of inferring sparse time-varying Markov random fiel...
In many applications, when building linear regression models, it is impo...
Ridge regularized sparse regression involves selecting a subset of featu...
The increasing use of machine learning in high-stakes domains – where
pe...
We consider the convex quadratic optimization problem with indicator
var...
We consider the problem of learning an optimal prescriptive tree (i.e., ...
Sensing systems powered by energy harvesting have traditionally been des...
Object detection is a critical problem for the safe interaction between
...
Decision trees are among the most popular machine learning models and ar...
In this paper, we study the problem of inferring time-varying Markov ran...
We study the minimization of a rank-one quadratic with indicators and sh...
Motivated by modern regression applications, in this paper, we study the...
We give safe screening rules to eliminate variables from regression with...
We consider the problem of learning optimal binary classification trees....
Sparse regression models are increasingly prevalent due to their ease of...
Signal estimation problems with smoothness and sparsity priors can be
na...
Grids allow users flexible on-demand usage of computing resources throug...