
On Random Subsampling of Gaussian Process Regression: A GraphonBased Analysis
In this paper, we study random subsampling of Gaussian process regressio...
01/28/2019 ∙ by Kohei Hayashi, et al. ∙ 16 ∙ shareread it

Einconv: Exploring Unexplored Tensor Decompositions for Convolutional Neural Networks
Tensor decomposition methods are one of the primary approaches for model...
08/13/2019 ∙ by Kohei Hayashi, et al. ∙ 8 ∙ shareread it

Data Interpolating Prediction: Alternative Interpretation of Mixup
Data augmentation by mixing samples, such as Mixup, has widely been used...
06/20/2019 ∙ by Takuya Shimada, et al. ∙ 4 ∙ shareread it

An Optimality Proof for the PairDiff operator for Representing Relations between Words
Representing the semantic relations that exist between two given words (...
09/19/2017 ∙ by Huda Hakami, et al. ∙ 0 ∙ shareread it

On Tensor Train Rank Minimization: Statistical Efficiency and Scalable Algorithm
Tensor train (TT) decomposition provides a spaceefficient representatio...
08/01/2017 ∙ by Masaaki Imaizumi, et al. ∙ 0 ∙ shareread it

Minimizing Quadratic Functions in Constant Time
A samplingbased optimization method for quadratic functions is proposed...
08/25/2016 ∙ by Kohei Hayashi, et al. ∙ 0 ∙ shareread it

Making Tree Ensembles Interpretable: A Bayesian Model Selection Approach
Tree ensembles, such as random forests and boosted trees, are renowned f...
06/29/2016 ∙ by Satoshi Hara, et al. ∙ 0 ∙ shareread it

Making Tree Ensembles Interpretable
Tree ensembles, such as random forest and boosted trees, are renowned fo...
06/17/2016 ∙ by Satoshi Hara, et al. ∙ 0 ∙ shareread it

A Tractable Fully Bayesian Method for the Stochastic Block Model
The stochastic block model (SBM) is a generative model revealing macrosc...
02/06/2016 ∙ by Kohei Hayashi, et al. ∙ 0 ∙ shareread it

Bayesian Masking: Sparse Bayesian Estimation with Weaker Shrinkage Bias
A common strategy for sparse linear regression is to introduce regulariz...
09/03/2015 ∙ by Yohei Kondo, et al. ∙ 0 ∙ shareread it

Doubly Decomposing Nonparametric Tensor Regression
Nonparametric extension of tensor regression is proposed. Nonlinearity i...
06/19/2015 ∙ by Masaaki Imaizumi, et al. ∙ 0 ∙ shareread it

Rebuilding Factorized Information Criterion: Asymptotically Accurate Marginal Likelihood
Factorized information criterion (FIC) is a recently developed approxima...
04/22/2015 ∙ by Kohei Hayashi, et al. ∙ 0 ∙ shareread it

Factorized Asymptotic Bayesian Hidden Markov Models
This paper addresses the issue of model selection for hidden Markov mode...
06/18/2012 ∙ by Ryohei Fujimaki, et al. ∙ 0 ∙ shareread it

Estimation of lowrank tensors via convex optimization
In this paper, we propose three approaches for the estimation of the Tuc...
10/05/2010 ∙ by Ryota Tomioka, et al. ∙ 0 ∙ shareread it

Think Globally, Embed Locally  Locally Linear Metaembedding of Words
Distributed word embeddings have shown superior performances in numerous...
09/19/2017 ∙ by Danushka Bollegala, et al. ∙ 0 ∙ shareread it
Kohei Hayashi
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Machine Learning researcher at AI Research Center, National Institute of Advanced Industrial Science and Technology (AIST)