activity
20132026
most citedCOMBSS: Best Subset Selection via Continuous Optimization

2 citations · 3 across the 18 of their papers we have counts for

collaborators
Showing 2024Show all

5 papers · 1 filter

stat.AP2024

Rating Players of Counter-Strike: Global Offensive Based on Plus/Minus value

Hongyu Xu, Sarat Moka

We propose a player rating mechanism for Counter-Strike: Global Offensive (CS ), a popular e-sport, by analyzing players' Plus/Minus values. The Plus/Minus value represents the ave…

stat.ME2024

Continuous Optimization for Offline Change Point Detection and Estimation

Hans Reimann, Sarat Moka, Georgy Sofronov

This work explores use of novel advances in best subset selection for regression modelling via continuous optimization for offline change point detection and estimation in univaria…

stat.ME2024

Group COMBSS: Group Selection via Continuous Optimization

Anant Mathur, Sarat Moka, Benoit Liquet +1

We present a new optimization method for the group selection problem in linear regression. In this problem, predictors are assumed to have a natural group structure and the goal is…

stat.ME2024

Best Subset Solution Path for Linear Dimension Reduction Models using Continuous Optimization

Benoit Liquet, Sarat Moka, Samuel Muller

The selection of best variables is a challenging problem in supervised and unsupervised learning, especially in high dimensional contexts where the number of variables is usually m…

stat.ME2024

Spatial Autoregressive Model on a Dirichlet Distribution

Teo Nguyen, Sarat Moka, Kerrie Mengersen +1

Compositional data find broad application across diverse fields due to their efficacy in representing proportions or percentages of various components within a whole. Spatial depen…