Motivated by recent developments in manifold-valued regression we propose a family of nonparametric kernel-smoothing estimators with metric-space valued output including several robust versions. Depending on the choice of the output space and the metric the estimator reduces to partially well-known procedures for multi-class classification, multivariate regression in Euclidean space, regression...

In this paper, we propose the problem of domain transfer structured output learning and the first solution to solve it. The problem is defined on two different data domains sharing the same input and output spaces, named as source domain and target domain. The outputs are structured, and for the data samples of the source domain, the corresponding outputs are available, while for most data samp...

The most popular type of input method in Japan is kana-kanji conversion, conversion from a string of kana to a mixed kanjikana string. However there is no study using discriminative methods like structured SVMs for kana-kanji conversion. One of the reasons is that learning a discriminative model from a large data set is often intractable. However, due to progress of recent researches, large sca...

The systems industry has now experienced al most three decades of growth and devel opment. In that period, a 1 arge number of analysis tools and techniques have been proposed to aid the development process. Early systems were supported by analysis techniques which had been used for some time in precomputer systems. Next, the precomputer techniques 'were modified to meet some of the unique requi...

BACKGROUND/AIM Unusual responses to sensations can impact upon the daily activities for individuals with autism spectrum disorder. Current understandings of these sensory experiences have been drawn from the proxy reports from parents/caregivers, standardised self-report questionnaires and autobiographical accounts. As sensory experiences are intensely personal, the first-hand accounts of peopl...