1 citations · 3 across the 8 of their papers we have counts for
11 papers
Augmented Lagrangian methods for convex optimization with priority constraints via an infeasibility control framework
Yuya Yamakawa, Shota Yamanaka, Nobuo Yamashita
We consider convex optimization problems with prioritized equality constraints, which may be infeasible. In many applications, such as network optimization and image reconstruction…
An uncertainty model for positive-valued parameters with application to robust optimization
Tatsuya Tanaka, Huimin Li, Shota Yamanaka +2
Many practical optimization problems involve uncertain parameters that are strictly positive. However, the most common uncertainty sets used in robust optimization are the box and…
Blur Effects on User Performance in Target-Pointing Tasks
Ryuto Tomihari, Taiki Kinoshita, Yosuke Oba +2
In projectors and head-mounted displays, an out-of-focus image appears blurred. Even when a display itself is in focus, computer operation may be hindered if the display is far fro…
Skewed Dual Normal Distribution Model: Predicting Touch Pointing Success Rates for Targets Near Screen Edges and Corners
Nobuhito Kasahara, Shota Yamanaka, Homei Miyashita
Typical success-rate prediction models for tapping exclude targets near screen edges. However, design constraints often force such placements, and in scrollable user interfaces, an…
Skewed Dual Normal Distribution Model: Predicting 1D Touch Pointing Success Rate for Targets Near Screen Edges
Nobuhito Kasahara, Shota Yamanaka, Homei Miyashita
Typical success-rate prediction models for tapping exclude targets near screen edges; however, design constraints often force such placements. Additionally, in scrollable UIs any e…
Improving Data Quality via Pre-Task Participant Screening in Crowdsourced GUI Experiments
Takaya Miyama, Satoshi Nakamura, Shota Yamanaka
In crowdsourced user experiments that collect performance data from graphical user interface (GUI) interactions, some participants ignore instructions or act carelessly, threatenin…