29 citations · 79 across the 22 of their papers we have counts for
4 papers · 1 filter
Adaptive Minimax Regret against Smooth Logarithmic Losses over High-Dimensional -Balls via Envelope Complexity
Kohei Miyaguchi, Kenji Yamanishi
We develop a new theoretical framework, the \emph{envelope complexity}, to analyze the minimax regret with logarithmic loss functions and derive a Bayesian predictor that adaptivel…
Stable Geodesic Update on Hyperbolic Space and its Application to Poincare Embeddings
Yosuke Enokida, Atsushi Suzuki, Kenji Yamanishi
A hyperbolic space has been shown to be more capable of modeling complex networks than a Euclidean space. This paper proposes an explicit update rule along geodesics in a hyperboli…
High-dimensional Penalty Selection via Minimum Description Length Principle
Kohei Miyaguchi, Kenji Yamanishi
We tackle the problem of penalty selection of regularization on the basis of the minimum description length (MDL) principle. In particular, we consider that the design space of the…
Exact Calculation of Normalized Maximum Likelihood Code Length Using Fourier Analysis
Atsushi Suzuki, Kenji Yamanishi
The normalized maximum likelihood code length has been widely used in model selection, and its favorable properties, such as its consistency and the upper bound of its statistical…