Box Drawings for Learning with Imbalanced Data

1 code implementation • 13 Mar 2014 • Siong Thye Goh, Cynthia Rudin

The vast majority of real world classification problems are imbalanced, meaning there are far fewer data from the class of interest (the positive class) than from other classes.

General Classification imbalanced classification

Sparse Density Trees and Lists: An Interpretable Alternative to High-Dimensional Histograms

1 code implementation • 22 Oct 2015 • Siong Thye Goh, Lesia Semenova, Cynthia Rudin

We present sparse tree-based and list-based density estimation methods for binary/categorical data.

Density Estimation Vocal Bursts Intensity Prediction

A Minimax Surrogate Loss Approach to Conditional Difference Estimation

1 code implementation • 10 Mar 2018 • Siong Thye Goh, Cynthia Rudin

We present a new machine learning approach to estimate personalized treatment effects in the classical potential outcomes framework with binary outcomes.

QROSS: QUBO Relaxation Parameter Optimisation via Learning Solver Surrogates

no code implementations • 19 Mar 2021 • Tian Huang, Siong Thye Goh, Sabrish Gopalakrishnan, Tao Luo, Qianxiao Li, Hoong Chuin Lau

In this way, we are able capture the common structure of the instances and their interactions with the solver, and produce good choices of penalty parameters with fewer number of calls to the QUBO solver.

Traveling Salesman Problem