Ludwig Schmidt

Fast and Sample Near-Optimal Algorithms for Learning Multidimensional Histograms

2018 · arXiv (Cornell University)

We study the problem of robustly learning multi-dimensional histograms. A $d$-dimensional function $h: D \rightarrow \mathbb{R}$ is called a $k$-histogram if there exists a partition of the domain $D \subseteq \mathbb{R}^d$ into $k$ axis-aligned rectangles …

LAION-5B: An open large-scale dataset for training next generation image-text models

2022 · arXiv (Cornell University)

Groundbreaking language-vision architectures like CLIP and DALL-E proved the utility of training on large amounts of noisy image-text data, without relying on expensive accurate labels used in standard vision unimodal supervised learning. The resulting models …