18 citations · 46 across the 7 of their papers we have counts for
7 papers
Refinement of Hottopixx Method for Nonnegative Matrix Factorization Under Noisy Separability
Tomohiko Mizutani
Hottopixx, proposed by Bittorf et al. at NIPS 2012, is an algorithm for solving nonnegative matrix factorization (NMF) problems under the separability assumption. Separable NMFs ha…
Improved Analysis of Spectral Algorithm for Clustering
Tomohiko Mizutani
Spectral algorithms are graph partitioning algorithms that partition a node set of a graph into groups by using a spectral embedding map. Clustering techniques based on the algorit…
Convex Programming Based Spectral Clustering
Tomohiko Mizutani
Clustering is a fundamental task in data analysis, and spectral clustering has been recognized as a promising approach to it. Given a graph describing the relationship between data…
Efficient Preconditioning for Noisy Separable NMFs by Successive Projection Based Low-Rank Approximations
Tomohiko Mizutani, Mirai Tanaka
The successive projection algorithm (SPA) can quickly solve a nonnegative matrix factorization problem under a separability assumption. Even if noise is added to the problem, SPA i…
Robustness Analysis of Preconditioned Successive Projection Algorithm for General Form of Separable NMF Problem
Tomohiko Mizutani
The successive projection algorithm (SPA) has been known to work well for separable nonnegative matrix factorization (NMF) problems arising in applications, such as topic extractio…
Spectral Clustering by Ellipsoid and Its Connection to Separable Nonnegative Matrix Factorization
Tomohiko Mizutani
This paper proposes a variant of the normalized cut algorithm for spectral clustering. Although the normalized cut algorithm applies the K-means algorithm to the eigenvectors of a…
Ellipsoidal Rounding for Nonnegative Matrix Factorization Under Noisy Separability
Tomohiko Mizutani
We present a numerical algorithm for nonnegative matrix factorization (NMF) problems under noisy separability. An NMF problem under separability can be stated as one of finding all…