# See the Tree Through the Lines: The Shazoo Algorithm -- Full Version --

arXiv: https://arxiv.org/abs/1301.5160 · HTML: https://mlsanity.com/paper/1301.5160/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Jan 2013.

## Built on by (most cited first, 2 of 2)

- [Delayed Bandits: When Do Intermediate Observations Help?](https://mlsanity.com/paper/2305.19036/) (2023)
- [Fast Online Node Labeling for Very Large Graphs](https://mlsanity.com/paper/2305.16257/) (2023)

## Abstract (arXiv)

Predicting the nodes of a given graph is a fascinating theoretical problem with applications in several domains. Since graph sparsification via spanning trees retains enough information while making the task much easier, trees are an important special case of this problem. Although it is known how to predict the nodes of an unweighted tree in a nearly optimal way, in the weighted case a fully satisfactory algorithm is not available yet. We fill this hole and introduce an efficient node predictor, Shazoo, which is nearly optimal on any weighted tree. Moreover, we show that Shazoo can be viewed as a common nontrivial generalization of both previous approaches for unweighted trees and weighted lines. Experiments on real-world datasets confirm that Shazoo performs well in that it fully exploits the structure of the input tree, and gets very close to (and sometimes better than) less scalable energy minimization methods.