1 citations · 2 across the 21 of their papers we have counts for
Showing cs.LGShow all
3 papers · 1 filter
cs.LG2024
Distilling Long-tailed Datasets
Zhenghao Zhao, Haoxuan Wang, Yuzhang Shang +2
Dataset distillation aims to synthesize a small, information-rich dataset from a large one for efficient model training. However, existing dataset distillation methods struggle wit…
cs.LG2023
Learning Gradient Fields for Scalable and Generalizable Irregular Packing
Tianyang Xue, Mingdong Wu, Lin Lu +3
The packing problem, also known as cutting or nesting, has diverse applications in logistics, manufacturing, layout design, and atlas generation. It involves arranging irregularly…
cs.LG2020
Learning Calibrated Uncertainties for Domain Shift: A Distributionally Robust Learning Approach
Haoxuan Wang, Zhiding Yu, Yisong Yue +3
We propose a framework for learning calibrated uncertainties under domain shifts, where the source (training) distribution differs from the target (test) distribution. We detect su…