16 citations · 59 across the 10 of their papers we have counts for
5 papers · 1 filter
MABSplit: Faster Forest Training Using Multi-Armed Bandits
Mo Tiwari, Ryan Kang, Je-Yong Lee +4
Random forests are some of the most widely used machine learning models today, especially in domains that necessitate interpretability. We present an algorithm that accelerates the…
Faster Maximum Inner Product Search in High Dimensions
Mo Tiwari, Ryan Kang, Je-Yong Lee +5
Maximum Inner Product Search (MIPS) is a ubiquitous task in machine learning applications such as recommendation systems. Given a query vector and atom vectors in -dimension…
MLDemon: Deployment Monitoring for Machine Learning Systems
Antonio Ginart, Martin Zhang, James Zou
Post-deployment monitoring of ML systems is critical for ensuring reliability, especially as new user inputs can differ from the training distribution. Here we propose a novel appr…
BanditPAM: Almost Linear Time -Medoids Clustering via Multi-Armed Bandits
Mo Tiwari, Martin Jinye Zhang, James Mayclin +3
Clustering is a ubiquitous task in data science. Compared to the commonly used -means clustering, -medoids clustering requires the cluster centers to be actual data points an…
Block-Wise MAP Inference for Determinantal Point Processes with Application to Change-Point Detection
Jinye Zhang, Zhijian Ou
Existing MAP inference algorithms for determinantal point processes (DPPs) need to calculate determinants or conduct eigenvalue decomposition generally at the scale of the full ker…