Network flow theory has been used across a number of disciplines, including theoretical
computer science, operations research, and discrete math, to model not only problems in the …

To the best of our knowledge, there are no methods today for training differentially private
regression models on sparse input data. To remedy this, we adapt the Frank-Wolfe algorithm …

Nearest neighbor search is a cornerstone problem in computational geometry, non-
parametric statistics, and machine learning. For N points, exhaustive search requires …

Abstract Jump Point Search (JPS) is a well known symmetry-breaking algorithm that can
substantially improve performance for grid-based optimal pathfinding. When the input grid is …

We present a new connection between self-adjusting binary search trees (BSTs) and heaps,
two fundamental, extensively studied, and practically relevant families of data structures …

We study ranked enumeration of join-query results according to very general orders defined
by selective dioids. Our main contribution is a framework for ranked enumeration over a …

This book is an introduction to data structures and algorithms for functional languages, with
a focus on proofs. It covers both functional correctness and running time analysis. It does so …

Since the invention of the pairing heap by Fredman, Sedgewick, Sleator, and Tarjan [8], it
has been an open question whether this or any other simple “self-adjusting” heap supports …

Weighted search is an essential component of many fundamental and useful algorithms.
Despite this, it is relatively under explored as a computational effect, receiving not nearly as …

Relative Lempel-Ziv (RLZ) parsing is a dictionary compression method in which a string $ S
$ is compressed relative to a second string $ R $(called the reference) by parsing $ S $ into …