160 citations · 161 across the 4 of their papers we have counts for
5 papers
Developing a Ranking Problem Library (RPLIB) from a data-oriented perspective
Paul E. Anderson, Brandon Tat, Charlie Ward +2
We present an improved library for the ranking problem called RPLIB. RPLIB includes the following data and features. (1) Real and artificial datasets of both pairwise data (i.e., i…
Weight Set Decomposition for Weighted Rank Aggregation: An interpretable and visual decision support tool
Tyler Perini, Amy Langville, Glenn Kramer +2
The problem of interpreting or aggregating multiple rankings is common to many real-world applications. Perhaps the simplest and most common approach is a weighted rank aggregation…
On the Graph Laplacian and the Rankability of Data
Thomas R. Cameron, Amy N. Langville, Heather C. Smith
Recently, Anderson et al. (2019) proposed the concept of rankability, which refers to a dataset's inherent ability to produce a meaningful ranking of its items. In the same paper,…
Algorithms, Initializations, and Convergence for the Nonnegative Matrix Factorization
Amy N. Langville, Carl D. Meyer, Russell Albright +2
It is well known that good initializations can improve the speed and accuracy of the solutions of many nonnegative matrix factorization (NMF) algorithms. Many NMF algorithms are se…
Data Clustering via Principal Direction Gap Partitioning
Ralph Abbey, Jeremy Diepenbrock, Amy Langville +3
We explore the geometrical interpretation of the PCA based clustering algorithm Principal Direction Divisive Partitioning (PDDP). We give several examples where this algorithm brea…