35 citations · 43 across the 4 of their papers we have counts for
5 papers
Classic Graph Structural Features Outperform Factorization-Based Graph Embedding Methods on Community Labeling
Andrew Stolman, Caleb Levy, C. Seshadhri +1
Graph representation learning (also called graph embeddings) is a popular technique for incorporating network structure into machine learning models. Unsupervised graph embedding m…
Fair Classification with Group-Dependent Label Noise
Jialu Wang, Yang Liu, Caleb Levy
This work examines how to train fair classifiers in settings where training labels are corrupted with random noise, and where the error rates of corruption depend both on the label…
Splaying Preorders and Postorders
Caleb C. Levy, Robert E. Tarjan
Let be a binary search tree. We prove two results about the behavior of the Splay algorithm (Sleator and Tarjan 1985). Our first result is that inserting keys into an empty bin…
A Foundation for Proving Splay is Dynamically Optimal
Caleb C. Levy, Robert E. Tarjan
Consider the task of performing a sequence of searches in a binary search tree. After each search, we allow an algorithm to arbitrarily restructure the tree. The cost of executing…
Zip Trees
Robert E. Tarjan, Caleb C. Levy, Stephen Timmel
We introduce the zip tree, a form of randomized binary search tree that integrates previous ideas into one practical, performant, and pleasant-to-implement package. A zip tree is a…