23 citations · 99 across the 25 of their papers we have counts for
16 papers · 1 filter
Inducing a hierarchy for multi-class classification problems
Hayden S. Helm, Weiwei Yang, Sujeeth Bharadwaj +5
In applications where categorical labels follow a natural hierarchy, classification methods that exploit the label structure often outperform those that do not. Un-fortunately, the…
A partition-based similarity for classification distributions
Hayden S. Helm, Ronak D. Mehta, Brandon Duderstadt +5
Herein we define a measure of similarity between classification distributions that is both principled from the perspective of statistical pattern recognition and useful from the pe…
Graph matching between bipartite and unipartite networks: to collapse, or not to collapse, that is the question
Jesús Arroyo, Carey E. Priebe, Vince Lyzinski
Graph matching consists of aligning the vertices of two unlabeled graphs in order to maximize the shared structure across networks; when the graphs are unipartite, this is commonly…
Limit theorems for out-of-sample extensions of the adjacency and Laplacian spectral embeddings
Keith Levin, Fred Roosta, Minh Tang +2
Graph embeddings, a class of dimensionality reduction techniques designed for relational data, have proven useful in exploring and modeling network structure. Most dimensionality r…
Geodesic Learning via Unsupervised Decision Forests
Meghana Madhyastha, Percy Li, James Browne +4
Geodesic distance is the shortest path between two points in a Riemannian manifold. Manifold learning algorithms, such as Isomap, seek to learn a manifold that preserves geodesic d…
Vertex Classification on Weighted Networks
Hayden Helm, Joshua Vogelstein, Carey Priebe
This paper proposes a discrimination technique for vertices in a weighted network. We assume that the edge weights and adjacencies in the network are conditionally independent and…