279 citations · 302 across the 9 of their papers we have counts for
9 papers
Comparison of Lightweight Methods for Vehicle Dynamics-Based Driver Drowsiness Detection
Yutaro Nakagama, Daisuke Ishii, Kazuki Yoshizoe
Driver drowsiness detection (DDD) prevents road accidents caused by driver fatigue. Vehicle dynamics-based DDD has been proposed as a method that is both economical and high perfor…
Graph Energy-based Model for Substructure Preserving Molecular Design
Ryuichiro Hataya, Hideki Nakayama, Kazuki Yoshizoe
It is common practice for chemists to search chemical databases based on substructures of compounds for finding molecules with desired properties. The purpose of de novo molecular…
Meta Approach to Data Augmentation Optimization
Ryuichiro Hataya, Jan Zdenek, Kazuki Yoshizoe +1
Data augmentation policies drastically improve the performance of image recognition tasks, especially when the policies are optimized for the target data and tasks. In this paper,…
Practical Massively Parallel Monte-Carlo Tree Search Applied to Molecular Design
Xiufeng Yang, Tanuj Kr Aasawat, Kazuki Yoshizoe
It is common practice to use large computational resources to train neural networks, as is known from many examples, such as reinforcement learning applications. However, while mas…
Faster AutoAugment: Learning Augmentation Strategies using Backpropagation
Ryuichiro Hataya, Jan Zdenek, Kazuki Yoshizoe +1
Data augmentation methods are indispensable heuristics to boost the performance of deep neural networks, especially in image recognition tasks. Recently, several studies have shown…
ChemTS: An Efficient Python Library for de novo Molecular Generation
Xiufeng Yang, Jinzhe Zhang, Kazuki Yoshizoe +2
Automatic design of organic materials requires black-box optimization in a vast chemical space. In conventional molecular design algorithms, a molecule is built as a combination of…
Redesigning pattern mining algorithms for supercomputers
Kazuki Yoshizoe, Aika Terada, Koji Tsuda
Upcoming many core processors are expected to employ a distributed memory architecture similar to currently available supercomputers, but parallel pattern mining algorithms amenabl…
Scalable Parallel Numerical Constraint Solver Using Global Load Balancing
Daisuke Ishii, Kazuki Yoshizoe, Toyotaro Suzumura
We present a scalable parallel solver for numerical constraint satisfaction problems (NCSPs). Our parallelization scheme consists of homogeneous worker solvers, each of which runs…
Scalable Parallel Numerical CSP Solver
Daisuke Ishii, Kazuki Yoshizoe, Toyotaro Suzumura
We present a parallel solver for numerical constraint satisfaction problems (NCSPs) that can scale on a number of cores. Our proposed method runs worker solvers on the available co…