5 citations · 31 across the 30 of their papers we have counts for
7 papers · 1 filter
Multidimensional Scaling: Approximation and Complexity
Erik Demaine, Adam Hesterberg, Frederic Koehler +2
Metric Multidimensional scaling (MDS) is a classical method for generating meaningful (non-linear) low-dimensional embeddings of high-dimensional data. MDS has a long history in th…
Optimal-area visibility representations of outer-1-plane graphs
Therese Biedl, Giuseppe Liotta, Jayson Lynch +1
This paper studies optimal-area visibility representations of -vertex outer-1-plane graphs, i.e. graphs with a given embedding where all vertices are on the boundary of the oute…
Solving Machine Learning Problems
Sunny Tran, Pranav Krishna, Ishan Pakuwal +4
Can a machine learn Machine Learning? This work trains a machine learning model to solve machine learning problems from a University undergraduate level course. We generate a new t…
Yin-Yang Puzzles are NP-complete
Erik D. Demaine, Jayson Lynch, Mikhail Rudoy +1
We prove NP-completeness of Yin-Yang / Shiromaru-Kuromaru pencil-and-paper puzzles. Viewed as a graph partitioning problem, we prove NP-completeness of partitioning a rectangular g…
Continuous Flattening of All Polyhedral Manifolds using Countably Infinite Creases
Zachary Abel, Erik D. Demaine, Martin L. Demaine +4
We prove that any finite polyhedral manifold in 3D can be continuously flattened into 2D while preserving intrinsic distances and avoiding crossings, answering a 19-year-old open p…
Snipperclips: Cutting Tools into Desired Polygons using Themselves
Zachary Abel, Hugo Akitaya, Man-Kwun Chiu +7
We study Snipperclips, a computer puzzle game whose objective is to create a target shape with two tools. The tools start as constant-complexity shapes, and each tool can snip (i.e…