2 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.LG2024
CATS: Contextually-Aware Thresholding for Sparsity in Large Language Models
Donghyun Lee, Je-Yong Lee, Genghan Zhang +2
Large Language Models (LLMs) have dramatically advanced AI applications, yet their deployment remains challenging due to their immense inference costs. Recent studies ameliorate th…
cs.LG2022★ 2 cited
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…
cs.LG2022★ 2 cited
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…