454 citations · 5.5k across the 247 of their papers we have counts for
5 papers · 1 filter
Condition Number Analysis of Kernel-based Density Ratio Estimation
Takafumi Kanamori, Taiji Suzuki, Masashi Sugiyama
The ratio of two probability densities can be used for solving various machine learning tasks such as covariate shift adaptation (importance sampling), outlier detection (likelihoo…
Super-Linear Convergence of Dual Augmented-Lagrangian Algorithm for Sparsity Regularized Estimation
Ryota Tomioka, Taiji Suzuki, Masashi Sugiyama
We analyze the convergence behaviour of a recently proposed algorithm for regularized estimation called Dual Augmented Lagrangian (DAL). Our analysis is based on a new interpretati…
Efficient Construction of Neighborhood Graphs by the Multiple Sorting Method
Takeaki Uno, Masashi Sugiyama, Koji Tsuda
Neighborhood graphs are gaining popularity as a concise data representation in machine learning. However, naive graph construction by pairwise distance calculation takes r…
Dual Augmented Lagrangian Method for Efficient Sparse Reconstruction
Ryota Tomioka, Masashi Sugiyama
We propose an efficient algorithm for sparse signal reconstruction problems. The proposed algorithm is an augmented Lagrangian method based on the dual sparse reconstruction proble…
Lanczos Approximations for the Speedup of Kernel Partial Least Squares Regression
Nicole Kraemer, Masashi Sugiyama, Mikio Braun
The runtime for Kernel Partial Least Squares (KPLS) to compute the fit is quadratic in the number of examples. However, the necessity of obtaining sensitivity measures as degrees o…