159 citations · 244 across the 10 of their papers we have counts for
9 papers · 1 filter
From Sequential Nodes to GPU Batches: Parallel Branch and Bound for Optimal -Sparse GLMs
Jiachang Liu, Andrea Lodi
GPUs have significantly accelerated first-order methods for large-scale optimization, especially in continuous optimization. However, this success has not transferred cleanly to pr…
FastSurvival: Hidden Computational Blessings in Training Cox Proportional Hazards Models
Jiachang Liu, Rui Zhang, Cynthia Rudin
Survival analysis is an important research topic with applications in healthcare, business, and manufacturing. One essential tool in this area is the Cox proportional hazards (CPH)…
Amazing Things Come From Having Many Good Models
Cynthia Rudin, Chudi Zhong, Lesia Semenova +7
The Rashomon Effect, coined by Leo Breiman, describes the phenomenon that there exist many equally good predictive models for the same dataset. This phenomenon happens for many rea…
Fast and Interpretable Mortality Risk Scores for Critical Care Patients
Chloe Qinyu Zhu, Muhang Tian, Lesia Semenova +4
Prediction of mortality in intensive care unit (ICU) patients typically relies on black box models (that are unacceptable for use in hospitals) or hand-tuned interpretable models (…
OKRidge: Scalable Optimal k-Sparse Ridge Regression
Jiachang Liu, Sam Rosen, Chudi Zhong +1
We consider an important problem in scientific discovery, namely identifying sparse governing equations for nonlinear dynamical systems. This involves solving sparse ridge regressi…
Exploring and Interacting with the Set of Good Sparse Generalized Additive Models
Chudi Zhong, Zhi Chen, Jiachang Liu +2
In real applications, interaction between machine learning models and domain experts is critical; however, the classical machine learning paradigm that usually produces only a sing…
FasterRisk: Fast and Accurate Interpretable Risk Scores
Jiachang Liu, Chudi Zhong, Boxuan Li +2
Over the last century, risk scores have been the most popular form of predictive model used in healthcare and criminal justice. Risk scores are sparse linear models with integer co…
Fast Sparse Classification for Generalized Linear and Additive Models
Jiachang Liu, Chudi Zhong, Margo Seltzer +1
We present fast classification techniques for sparse generalized linear and additive models. These techniques can handle thousands of features and thousands of observations in minu…
CLUB: A Contrastive Log-ratio Upper Bound of Mutual Information
Pengyu Cheng, Weituo Hao, Shuyang Dai +3
Mutual information (MI) minimization has gained considerable interests in various machine learning tasks. However, estimating and minimizing MI in high-dimensional spaces remains a…