activity
20172022
most citedGeneralized Linear Rule Models

16 citations · 34 across the 6 of their papers we have counts for

collaborators
Showing cs.LGShow all

5 papers · 1 filter

cs.LG20221 cited

Bayesian Experimental Design for Symbolic Discovery

Kenneth L. Clarkson, Cristina Cornelio, Sanjeeb Dash +3

This study concerns the formulation and application of Bayesian optimal experimental design to symbolic discovery, which is the inference from observational data of predictive mode…

cs.LG2021

Integer Programming for Causal Structure Learning in the Presence of Latent Variables

Rui Chen, Sanjeeb Dash, Tian Gao

The problem of finding an ancestral acyclic directed mixed graph (ADMG) that represents the causal relationships between a set of variables is an important area of research on caus…

cs.LG20203 cited

Symbolic Regression using Mixed-Integer Nonlinear Optimization

Vernon Austel, Cristina Cornelio, Sanjeeb Dash +4

The Symbolic Regression (SR) problem, where the goal is to find a regression function that does not have a pre-specified form but is any function that can be composed of a list of…

cs.LG2020

Multilabel Classification by Hierarchical Partitioning and Data-dependent Grouping

Shashanka Ubaru, Sanjeeb Dash, Arya Mazumdar +1

In modern multilabel classification problems, each data instance belongs to a small number of classes from a large set of classes. In other words, these problems involve learning v…

cs.LG201916 cited

Generalized Linear Rule Models

Dennis Wei, Sanjeeb Dash, Tian Gao +1

This paper considers generalized linear models using rule-based features, also referred to as rule ensembles, for regression and probabilistic classification. Rules facilitate mode…